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GEMBA CONCEPTS

Experience: ~3–5 years Type: Full-time

AI/ML Engineer

Location: Bengaluru, India (Hybrid)

About Gemba Concepts

Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics

modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing

traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a

tight engineering team that ships real systems for demanding, often regulated, environments.

The Role

We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the

problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy

industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.

What You’ll Do

Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under

real factory lighting, throughput, and edge-case conditions.

Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure

prediction.

Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.

Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.

Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they

add leverage.

Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to

know when ML is not the right answer.

Communicate results and limitations clearly to non-ML stakeholders, including clients.

What We’re Looking For

3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).

Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.

Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /

anomaly detection.

Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /

Kubernetes (AKS) is a strong plus.

Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production

reality.

Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.

Nice to Have

Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).

Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).

Edge deployment experience (running CV models on-device / near the line).

Exposure to data pipeline tooling and orchestration.

What You’ll Get

Real ownership of ML systems that go into production for serious clients.

A lean, senior-heavy team where you ship fast and learn across the stack.

Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact

GEMBA CONCEPTS

Experience: ~3–5 years Type: Full-time

AI/ML Engineer

Location: Bengaluru, India (Hybrid)

About Gemba Concepts

Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics

modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing

traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a

tight engineering team that ships real systems for demanding, often regulated, environments.

The Role

We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the

problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy

industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.

What You’ll Do

Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under

real factory lighting, throughput, and edge-case conditions.

Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure

prediction.

Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.

Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.

Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they

add leverage.

Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to

know when ML is not the right answer.

Communicate results and limitations clearly to non-ML stakeholders, including clients.

What We’re Looking For

3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).

Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.

Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /

anomaly detection.

Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /

Kubernetes (AKS) is a strong plus.

Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production

reality.

Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.

Nice to Have

Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).

Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).

Edge deployment experience (running CV models on-device / near the line).

Exposure to data pipeline tooling and orchestration.

What You’ll Get

Real ownership of ML systems that go into production for serious clients.

A lean, senior-heavy team where you ship fast and learn across the stack.

• Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact

Role Overview

We are looking for a Junior AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations.

This role offers an opportunity to work closely with experienced engineers, product teams, and AI specialists on real AI-powered systems that support learners, educators, schools, and internal business operations.

At GoSuper EdTech, our cloud infrastructure is built on Google Cloud Platform — GCP. You will get hands-on exposure to GCP-based systems, backend services, AI integrations, deployment workflows, monitoring, cloud storage, databases, and automation pipelines.

You will help design, integrate, test, monitor, and maintain AI-enabled systems using modern tools such as AI APIs, LLMs, automation workflows, backend services, databases, GCP services, cloud deployment tools, and monitoring systems.

This role is ideal if you are curious about AI, comfortable with technical problem-solving, and interested in building reliable systems that connect software, data, cloud infrastructure, automation, and intelligent workflows.

What You’ll Do

• Support the development and maintenance of AI-powered systems, tools, and workflows.
• Assist in integrating AI APIs, LLM platforms, automation tools, and backend services into GoSuper products.
• Work with OpenAI, Gemini, Claude, or similar AI platforms under the guidance of senior engineers.
• Support AI and backend workflows deployed on Google Cloud Platform — GCP.
• Assist with GCP-based services such as Cloud Run, Compute Engine, Cloud Functions, Cloud Storage, Firebase, Firestore, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, and Cloud Monitoring, based on project needs.
• Help build AI workflows for content generation, chatbot systems, smart recommendations, internal automation, and productivity tools.
• Support backend integrations using Node.js, Python, REST APIs, webhooks, and third-party services.
• Assist in designing and maintaining system workflows that connect databases, applications, AI models, cloud services, and business tools.
• Work with databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or similar platforms.
• Help test AI outputs, validate workflows, debug issues, and improve system reliability.
• Monitor system performance, API usage, errors, logs, workflow failures, and cloud service health.
• Support deployment, configuration, and maintenance of AI-enabled product features on GCP.
• Collaborate with product managers, developers, designers, QA teams, and business teams to understand requirements and deliver working solutions.
• Participate in daily standups, sprint planning, technical discussions, and team meetings.
• Document AI workflows, system logic, API integrations, prompts, GCP configurations, deployment steps, and troubleshooting processes.
• Continuously learn and apply best practices in AI systems, backend engineering, automation, GCP cloud infrastructure, and production support.

What We’re Looking For

• 6 months to 1 year of experience in AI systems, backend development, software engineering, automation, DevOps support, cloud support, system integration, or relevant internship/project experience.
• Basic understanding of AI tools, LLMs, APIs, automation workflows, and software systems.
• Working knowledge of JavaScript, TypeScript, or Python.
• Basic backend development experience with Node.js, Express, NestJS, FastAPI, or similar frameworks.
• Basic understanding of Google Cloud Platform — GCP or willingness to learn GCP-based deployment and monitoring workflows.
• Understanding of REST APIs, webhooks, third-party integrations, and data flow between systems.
• Interest in AI APIs, prompt workflows, chatbot systems, automation tools, and intelligent product features.
• Basic understanding of databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or Redis.
• Ability to debug technical issues across APIs, workflows, logs, backend services, and cloud deployments.
• Good analytical thinking and problem-solving ability.
• Ability to write clear documentation for workflows, integrations, cloud configurations, and technical processes.
• Eagerness to learn new tools, AI platforms, system design concepts, GCP services, and cloud technologies.
• Good communication skills to work with technical and non-technical teams.
• Ownership mindset and willingness to take responsibility for assigned tasks.
• Comfortable working in a fast-paced startup environment.

Nice to Have

• Familiarity with AI APIs such as OpenAI, Gemini, Claude, or similar platforms.
• Basic understanding of prompt engineering and LLM-based workflows.
• Exposure to LangChain, LlamaIndex, embeddings, vector databases, or retrieval-augmented generation.
• Basic experience with GCP services such as Cloud Run, Cloud Functions, Firebase, Firestore, Cloud Storage, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, or Cloud Monitoring.
• Exposure to Google AI tools, Vertex AI, Gemini API, or AI-related services on GCP.
• Experience with automation tools, workflow builders, webhooks, or integration platforms.
• Exposure to Docker, CI/CD pipelines, GitHub Actions, deployment workflows, or cloud-based release processes.
• Experience working with logs, monitoring tools, API testing tools, or debugging platforms.
• Familiarity with Postman, Git, GitHub, Notion, Zoho, Slack, or similar productivity tools.
• Experience building chatbots, AI assistants, internal tools, or automated workflows.
• Personal, academic, internship, or open-source projects related to AI, automation, backend systems, GCP, or cloud tools.
• Interest in SaaS, EdTech, AI-powered products, and startup environments.

What You’ll Gain

• Hands-on experience building AI-powered systems in a real startup environment.
• Practical exposure to AI APIs, LLM workflows, automation systems, backend services, and GCP cloud infrastructure.
• Mentorship from senior engineers and product leaders.
• Experience working across AI, backend engineering, databases, APIs, integrations, deployment, system monitoring, and cloud operations.
• Opportunity to contribute to real product features used by learners, educators, schools, and institutions.
• Exposure to SaaS product development, EdTech workflows, AI-driven business solutions, and GCP-based production systems.
• Learning culture that encourages experimentation, feedback, and continuous improvement.
• Opportunity to understand how AI systems are designed, deployed, monitored, scaled, and improved in production.
• Access to Cult Elite and Cult Play Pass, offering wellness and lifestyle benefits to keep you energized and inspired.

Compensation

• Competitive salary with performance-based bonuses.
• Equity ownership through ESOPs — own a piece of the company you help build.
• Flexible remote work options with occasional Bengaluru office meetups.
• Health and wellness perks, including Cult Elite membership and Cult Play Pass for employees.
• Learning and development support to help you grow in AI systems, backend engineering, automation, SaaS, and GCP cloud technologies.
• Team retreats, virtual hangouts, and a collaborative work culture.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

Are you looking to work in the cutting edge area of applying data-science to help global customers get a better insight into their health? If so, read on and apply.

Role Name: Senior Data Scientist

Science Team | Full-Time | In-Office | Bangalore

The Role

The Ultrahuman Science Team builds the algorithms behind the Ring, M1 CGM, blood and urine biomarkers, and Performance Lab assessments. We are hiring a Senior Data Scientist to own those algorithms end to end: from the raw sensor signal to a model that is shipped, monitored, and trusted in users' hands.

This is a build role with real scope. In a typical month you will improve a production algorithm, root-cause a metric users are complaining about, and stand up the data pipeline the next model needs. The common thread is ownership: you take a vague question and return a working answer, without waiting to be handed scope.

What You'll Do

·      Own algorithms end to end: sleep staging, activity detection, sensor-derived metrics, and health scores. You frame the problem, build the features, train and evaluate the model, and see it live

·      Ship models, not notebooks: you prove a change on our own cohort before it reaches users, and a model is done only when it runs in production and you can tell how it is behaving

·      Validate against reference standards: design evaluations against gold standards, reference devices, and study ground truth, and know when a result is real and when it is an artifact

·      Own the data layer: cohort extraction, feature pipelines, study data, and raw sensor data, so the next model starts from clean inputs

What This Looks Like in Practice

1. Improving production algorithms - Take an existing production model like sleep staging, root-cause the failure modes against reference data, and ship a fix you can defend with numbers.

2. Building new models - Train an activity classifier on raw sensor data, design the labeled data collection that expands it, and pick the operating point so false positives never erode trust.

3. Proving it before it ships - Run a new steps algorithm against reference-device cohorts, decide with data when it is ready, and monitor how it behaves after rollout.

Who You Are

The two things we can't coach

·      High ownership, end to end: you take a problem from a vague question to a shipped model without waiting to be handed scope, and you can point to something you owned from raw data all the way to production

·      Hungry for more scope: you have outgrown your current role and want problems biggerthan your title, with the technical depth to be trusted with them

Also important

·      You've worked with human health data: wearables, physiological signals, or clinical data.

If your experience is close but not exact, show us why you will ramp fast

·      You've built at a startup: or somewhere small enough that nobody handed you clean data, clear specs, or a mature ML platform

·      You work like it's 2026: coding agents and AI tooling are part of how you build every day, and you can tell which new capabilities are worth adopting

·      You communicate: you can explain a model and its limits to a product manager, an engineer, or a founder, and hold your own with our scientists Core Technical Skills

·      Languages and data: Python and SQL daily, comfortable working in a real codebase

·      Machine learning: PyTorch or TensorFlow, scikit-learn, and gradient boosting, with the judgment to know which the problem needs

·      Advanced machine learning: time series and sequence models, deep learning on continuous physiological signals, and ensembles

·      Statistics and evaluation: hypothesis testing, experiment and A/B design, model evaluation, and error analysis against a reference standard

·      Scale and cloud: Spark or equivalent on large datasets, and AWS, GCP, or Azure

·      Production ML and MLOps: training pipelines, model versioning, deployment, monitoring, and drift detection

·      LLMs and agentic systems: fine-tuning and serving models, building agentic pipelines, and using coding agents to move faster

Experience:

- 4 to 5 years building and shipping machine learning systems. We index on what you have shipped and on trajectory, not the exact number of years; if you are a little earlier but have clearly outgrown your current scope, we want to hear from you.

- Bachelor's or higher in engineering, computer science, statistics, or a related field.

How We Work and Who Thrives Here

- The Science team is small and moves fast, and much of the work has no precedent to copy.

- People do their best work here when they are energized by ambiguity, low on ego, quick to adopt a better idea no matter where it comes from, and comfortable owning something before anyone has told them how. If you need a mature data org, clean labelled datasets, and clear guardrails to thrive, this particular role will not be the right fit, and that is worth knowing up front.

What You'll Gain

·      Ownership of algorithms that hundreds of thousands of people see every morning

·      A dataset most scientists never get to touch: 100M+ nights of sleep and continuous physiological signals at scale

·      Direct collaboration with the engineering, product, and design teams building Ultrahuman

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. 

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

Job application link : https://grnh.se/z7qx2ehx1us

Company: CombineHealth AI

Location: Bangalore, India (Work from Office — 4 days/week)

Experience: 3+ years

Employment Type: Full-time

About Combine Health

Combine Health is building an AI workforce for healthcare revenue cycle management (RCM) — agentic AI systems that automate medical coding, billing, claims, and denial management, and reason through payer policy for healthcare providers in the US. Backed by Y Combinator and Silicon Valley investors, we work with hospitals and health systems to eliminate revenue leakage and reduce manual, error-prone billing work.

We're a small, fast-moving team. Every engineer here owns real product surface area from day one — there's no hiding behind process at a 12-person company.

The Role

We're looking for a Full Stack Engineer to build and ship features across our AI-driven RCM platform — from the interfaces our customers use to review claims and denials, to the backend services that power our AI agents. You'll work closely with founders and a small engineering team, moving fast on a product that directly affects hospital cash flow.

This is not a role where requirements arrive fully specified. You'll be expected to help define what to build, not just how.

What You'll Do

• Design, build, and ship full stack features across the product — from UI to APIs to data models
• Build interfaces for complex, data-heavy workflows (claims review, denial queues, coding dashboards) that need to be fast and legible, not just functional
• Work with backend services that integrate with AI agents, payer systems, and healthcare data sources
• Own features end-to-end: design, implementation, testing, deployment, and iteration based on customer feedback
• Collaborate directly with founders and product on prioritization — this isn't a "tickets handed to you" role
• Write clean, maintainable code and help set engineering practices as the team scales
• Debug and resolve production issues quickly in a live, customer-facing system

What We're Looking For

• 3+ years of professional experience building full stack web applications in production
• Strong hands-on experience with a modern frontend framework (React or similar) and backend framework/language (Python, Node.js or similar)
• Comfort working across the stack: REST/GraphQL APIs, relational databases (Postgres/MySQL), and basic infra/deployment (Docker, cloud platforms like AWS/GCP)
• Ability to take a loosely defined problem and ship a working solution without waiting for a detailed spec
• Solid fundamentals in data modeling, system design, and debugging complex issues in production
• Startup mindset: comfortable with ambiguity, fast iteration, and wearing multiple hats
• Strong communication — you'll be working directly with a small team and need to explain trade-offs clearly

Good to have:

• Experience integrating with AI/LLM APIs or building AI-adjacent product features
• Prior experience at an early-stage startup (seed to Series A)

Why Join Combine Health

• Work on a product with real, measurable impact — faster payments, fewer denials, less manual work for healthcare teams
• Small team, high ownership — your work ships and matters immediately
• Backed by Y Combinator and top investors, early enough that your decisions shape the product
• Direct access to founders and fast decision-making, no layers of bureaucracy

How to apply

• Please click on the link and fill in the details: https://forms.gle/8tX3sXpFZQKotB9e9 

To apply, share your resume along with links to relevant projects or GitHub/portfolio.

Job Description

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop data processing solutions using Python.
• Write complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain data ingestion and integration workflows.
• Implement data quality, validation, monitoring, and error-handling processes.
• Develop and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
• Collaborate with data analysts, data scientists, software engineers, and business teams.
• Optimize data pipelines for performance, reliability, and scalability.
• Troubleshoot production data issues and ensure timely resolution.
• Follow best practices for version control, code quality, testing, and deployment.

Mandatory Skills

• Python
• ETL
• SQL
• CI/CD
• DevOps
• Git / Version Control
• Strong problem-solving and debugging skills

Job Summary

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.

Experience with Google Cloud Platform (GCP) will be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Develop complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain reliable data integration workflows across multiple data sources.
• Perform data cleansing, validation, transformation, and quality checks.
• Analyze data and provide insights to support business and technical requirements.
• Implement and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
• Troubleshoot data pipeline failures, performance issues, and production incidents.
• Optimize data processing workflows for performance, scalability, and reliability.
• Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
• Follow best practices for version control, testing, documentation, and deployment.
• Contribute to cloud-based data engineering initiatives, preferably on GCP.

Required Skills

• 5–7 years of hands-on experience in Data Engineering.
• Strong programming skills in Python.
• Strong expertise in Advanced SQL and database concepts.
• Hands-on experience with ETL/ELT processes and data pipelines.
• Good understanding of Data Warehousing and Data Modeling concepts.
• Experience with CI/CD practices and tools.
• Strong understanding of DevOps principles, automation, and deployment processes.
• Strong data analytics and problem-solving skills.
• Experience working with large datasets and performance optimization.
• Good understanding of Git/version control and software development best practices.

Good to Have

• Hands-on experience with Google Cloud Platform (GCP).
• Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
• Experience with containerization/orchestration technologies such as Docker/Kubernetes.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of cloud-based data architecture and distributed data processing.

Preferred Candidate Profile

• Strong analytical and problem-solving abilities.
• Good communication and stakeholder management skills.
• Ability to work independently as well as in a collaborative team environment.
• Strong ownership of data pipelines and production systems.
• Candidates who can join at short notice are preferred.

Mandatory Skills

 Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops

About Us

Invorto is our Voice AI product, bringing intelligent voice agents to real-world customer and operational use cases. Our voice pipeline is built in Python, running an STT → LLM → TTS architecture on top of the Pipecat framework.

This is a chance to work on hard problems in voice AI — latency, accuracy, naturalness, and reliability — building zero-to-one, owning your area end-to-end, and shipping to production at scale.

Note: This is a customer-facing role, and strong communication skills are essential.

About the Role

We're looking for a Voice AI Research Engineer to join the Invorto team and help build and continuously improve the voice AI systems that power our intelligent voice agents. This role is focused on the specialized craft of voice AI — designing evaluation and automation frameworks that ensure our STT, LLM, and TTS pipeline performs reliably in real-world, production conditions.

What You'll Do

• Design and build automated testing and quality frameworks for our STT → LLM → TTS voice pipeline, built on Pipecat
• Evaluate and benchmark STT, LLM, and TTS/ASR components on accuracy, latency, naturalness, and robustness across accents, languages, and real-world audio conditions
• Work hands-on with STT, TTS, and ASR models — fine-tuning, evaluating, and improving them for production use cases
• Identify failure modes and edge cases across the pipeline (background noise, accents, interruptions, turn-taking, latency, pipeline-stage handoffs) and build systems to catch them before production
• Collaborate closely with engineering to integrate quality checks and automation into the voice agent development lifecycle within the Pipecat-based architecture
• Research and stay current with advances in voice AI, and bring in new techniques, models, and tools to improve pipeline performance
• Work directly with customers to understand real-world voice use cases and translate them into evaluation criteria and quality benchmarks
• Partner with product and engineering to define what "production-grade quality" means for voice agents and drive the team toward it

What We're Looking For

• 4–6 years of experience, with a specialization in voice AI systems and automated quality evaluation
• Hands-on experience with STT (Speech-to-Text), TTS (Text-to-Speech), and ASR (Automatic Speech Recognition) models
• Experience designing and building automated testing/evaluation frameworks for voice or speech systems
• Strong understanding of what drives voice AI quality — accuracy, latency, naturalness, and robustness to real-world variability
• Strong programming skills in Python; familiarity with Pipecat or similar voice pipeline/orchestration frameworks is a plus
• Understanding of STT → LLM → TTS pipeline architectures and the trade-offs involved at each stage
• Research mindset — comfortable exploring new models, techniques, and tools and translating them into practical improvements
• Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and validate quality expectations

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a QA Engineer who specializes in testing agentic AI platforms. You will design and automate quality processes for systems that involve LLMs, autonomous agents, tool use and orchestration across Lumen and Agent Studio — ensuring that AI-driven workflows behave reliably, safely and predictably in production, not just in a demo.

What You’ll Do

• Design and build automated test suites and evaluation frameworks for agentic AI workflows, including multi-step and tool-calling behaviors.
• Use AI/LLM-based QA tools and evaluation frameworks to test model outputs, agent decisions and end-to-end task completion at scale.
• Define quality metrics and benchmarks for agent reliability, correctness, latency and safety, and track them over releases.
• Identify edge cases, failure modes and regressions specific to non-deterministic AI systems, and build automated checks to catch them early.
• Integrate automated agent/LLM testing into CI/CD pipelines to support fast, reliable iteration.
• Partner closely with AI/ML and backend engineers to reproduce issues, root-cause failures and validate fixes.
• Work with customers and customer-facing teams to understand real-world usage patterns and translate them into test scenarios.

What We’re Looking For

• 2–4 years of QA/test automation experience, including hands-on work testing agentic AI or LLM-based platforms.
• Practical experience using AI-focused QA/evaluation tools to test agent behavior, prompts and model outputs.
• Strong scripting/automation skills (Python preferred) to build and maintain test frameworks.
• Understanding of how LLM-based agents work — tool calling, orchestration, memory, reasoning chains — well enough to design meaningful test cases.
• Comfort working with non-deterministic systems and designing evaluation approaches beyond traditional pass/fail testing.
• Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

• Experience testing voice AI or real-time conversational systems.
• Familiarity with CRM or enterprise SaaS platforms.
• Exposure to enterprise security or compliance testing for AI systems.

About us

MyRico builds personal AI agents for enterprise, the copilots and digital employees that make humans more productive. The MyRico agents sit at the intersection of enterprise memory, high-end security, and an ever-expanding set of capabilities. We're a small team shipping fast, and the product is live with real customers today.

The role

Full-time · Bangalore

You'll own the systems that make an autonomous agent trustworthy in production. This is not just prompt engineering, and it's not model training - it's that and all the engineering layers in between: model steering, memory architecture, orchestration design, latency optimization, deterministic vs non-deterministic systems tradeoff, deployment, and operator tooling.

Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.

What we're looking for

• More than 7 years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.
• Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.
• Python and shell in production settings; comfortable in TypeScript/Node. You write boring, testable code and prefer the standard library to a new dependency.
• Systems taste: append-only logs, idempotent reconciliation, fold-the-events state machines, and read-only debugging surfaces feel like home.
• Evidence discipline: tests before features, claims backed by quoted observations, decisions written down.

Nice to have

• Experience running the combination of multi-tenant and single-tenant / on-prem-style fleets with ability to handle per-customer isolation, upgrade paths, migration compatibility in both setups.
• Security instincts for products that touch highly sensitive data and systems, including things like executives' email, calendars, and messages: least privilege, loopback-only services, secrets that never hit a log.
• You already orchestrate AI coding agents in your own workflow and have opinions about where they break.

How we work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation, your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

Must of Skills/Experience 

• System Design

• Python

• TensorFlow

• Google ADK or Lang Graph

• Lang Chain , Lang Graph

• Spark

• Agentic AI Design

• ML Ops

• MCP (client and server)

• FastAPI

• Doc Factory

• RAG

• Golang

• LLMs – Gemini, Open AI

• NLP

• Dev Assistant - AI based code - generation

(Qwen or Claude or Copilot)

• CI/CD

• Good in oral and written communication,

collaboration and be a team player

Good to have skills 

• DevOps with K8

• Scripting

• Java

• REST API

• UV

• ReACT

• DocFactory

• Unix

Senior Software Engineer (Full Stack)

Location: Bangalore / Chennai / Pune / Hyderabad

Experience: 7+ Years

Notice Period: Immediate Joiner

Job Summary:

We are looking for a Senior Software Engineer with strong Full Stack development expertise in Streamlit, Python FastAPI, Databricks, and Databricks Apps. The ideal candidate will build data-driven web applications and deploy scalable solutions within the Databricks ecosystem.

Key Responsibilities:

• Design and develop interactive applications using Streamlit.
• Build scalable backend services and APIs using Python FastAPI.
• Develop and optimize data solutions on Databricks.
• Deploy and manage applications using Databricks Apps (Mandatory).
• Integrate front-end applications with backend APIs and data services.
• Collaborate with data engineers, data scientists, and business teams.
• Ensure application performance, reliability, and security.
• Participate in code reviews, testing, and release management activities.

Required Skills:

• 7+ years of software development experience.
• Strong experience with Python programming.
• Hands-on expertise in FastAPI.
• Experience developing applications using Streamlit.
• Strong Databricks development experience.
• Mandatory experience with Databricks Apps deployment and management.
• Experience with REST APIs and microservices architecture.
• Familiarity with Git, CI/CD pipelines, and Agile methodologies.

Preferred Skills:

• Experience with Azure Databricks.
• Knowledge of AI/ML application development.
• Understanding of cloud-native architectures.
• Front End: Streamlit
• Middleware: Python FastAPI
• Backend: Databricks
• Hosting Environment: Databricks Apps (Mandatory)

Job Description:

Experience: 10+ Years

Job Summary

We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.

Key Responsibilities

• Design end-to-end data architecture using Microsoft Fabric.
• Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
• Define data ingestion, ETL/ELT, governance, security, and performance strategies.
• Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
• Work with business stakeholders to translate requirements into technical solutions.
• Mentor engineering teams and provide technical leadership.

Required Skills

• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
• Azure Data Engineering
• Power BI
• Azure AI Services / Azure OpenAI
• Data Architecture & Data Modeling
• SQL, Python
• Azure DevOps, CI/CD
• Strong stakeholder management and solution design experience
• 
  

Preferred: Experience in Capital Markets or Financial Services and Microsoft Azure/Fabric certifications.

NOTE: One technical round is mandatory to be taken F2F from office.

Location: Pune/Bengaluru

As a Software Engineer, you will tackle a highly challenging role within our Cyber Security Engineering integration development team. You will be responsible for the End-to-End (E2E) delivery of projects from gathering customer requirements to deploying high-performance data exchange solutions on-prem or in the cloud. We are looking for a Systems-Level Thinker who can seamlessly transition between building complex integrations and architecting high-throughput, low-latency backends. Because each integration may require a different technical approach, we value engineers who love reskilling, following agile best practices, and maintaining an evolving mindset.

Core Responsibilities

Customer and Stakeholder Collaboration

● Customer Delight: Maintain a strong customer-first attitude while designing, building, and deploying products.

● Technical Communication: Articulate complex technical trade-offs clearly to both business stakeholders and engineering teams.

● Pipeline Management: Manage customer relationships effectively to ensure a continuous flow of project scope, maintaining clear team backlogs.

Job Requirements

● Experience: 3+ years of proven software engineering experience, with a track record of leading small engineering teams or mentoring junior devs.

● High-Throughput Backend Focus: 3+ years of experience engineering robust, real-time backends specifically using Go (Golang) or Java.

● Polyglot and Integration Capability: Deep expertise in at least one or two additional languages/frameworks from our ecosystem: Python, TypeScript, Node.js, React.js, Angular, C#, or C++.

● Computer Science Fundamentals: Excellent knowledge of complex Data Structures, algorithms, and their correct situational usage.

● Adaptability: A passionate programmer who is genuinely open and excited to learn new software development skills as required by changing project demands.

Bonus / Added Advantages

● AI & Intelligent Automation: Hands-on knowledge of AI concepts, Large Language Models (LLMs), and experience building or integrating AI agents to automate complex workflows or security processes.

● Cybersecurity Domain: Experience in the cybersecurity space (SIEM, SOAR, or platform security).

● Modern Web Tech: Strong experience in developing software using modern web technologies.

● E2E Lifecycle: Proven background handling a project completely from discovery to cloud/on-prem deployment.

● Open Source: Active contributions to the Open Source community. (Please share your GitHub/GitLab links in your application!)

Job Title: AI Engineer Intern

Location: Bangalore(Onsite)

Experience Level: Recent Graduates.

Salary Range: 25K/month

Application Link:https://beyond.ciltriq.com/apply/fit

Description:

Join an early-stage, high-velocity team building AI agents that automate end-to-end compliance investigations for banks.

The product is already live, and you'll work directly on the core platform-building and evaluating agent systems that power real compliance investigations.

This is a hands-on engineering role with real ownership, working on production systems from day one.

6 Months Internship.

Full time offer based on Performance.

Requirements:

- Build and improve agent harness for compliance investigation use cases

- Develop and evaluate LLM-based extraction, classification, and reasoning components

- Contribute to synthetic data generation for agent testing and evaluation

- Write evaluation harnesses to measure agent accuracy and reasoning quality

- Document agent behaviour, evaluation results, and design decisions

- Track latest agentic AI research and bring relevant techniques into production (context management, long-term memory, agent learning)

- Train and fine-tune machine learning models from scratch for compliance-specific use cases

- Strong foundation in Python; comfortable with ML libraries

- Exposure to or strong curiosity about LLMs and agentic frameworks

- Independent – able to own problems, not just sub-tasks, in a small team

- Good written communication; able to document and present your work clearly

- Prior coursework or projects in ML, NLP, or distributed systems is a plus

- No prior fintech or compliance experience required

AI Engineer (Preferred Years of Experience: 8 years)

We are seeking a highly skilled Full Stack AI Engineer to design, build, and scale intelligent applications across the full technology stack. This role combines strong backend and frontend engineering expertise with applied AI/ML implementation in enterprise cloud environments.

You will work closely with product managers, architects, data scientists, and DevOps teams to deliver production-grade AI-powered solutions that are secure, scalable, and aligned with business objectives.

This is a hands-on engineering role requiring experience across application development, AI model integration, cloud architecture, and DevSecOps practices.

Key Responsibilities

AI / Machine Learning

• Design and implement AI/ML solutions for real-world business use cases.
• Integrate ML models (e.g., forecasting, classification, NLP, computer vision) into production-grade applications.
• Develop APIs and services that expose AI capabilities securely and efficiently.
• Optimize model performance, latency, scalability, and monitoring in production.
• Implement model lifecycle management (training, deployment, monitoring, retraining).

Backend Development

• Design and develop scalable RESTful and/or GraphQL APIs.
• Build microservices-based architectures.
• Implement authentication, authorization, and secure API access.
• Develop data pipelines and integrate with structured and unstructured data sources.
• Ensure high availability, performance tuning, and observability.

Frontend Development

• Develop responsive, user-friendly web applications.
• Build interactive dashboards and AI-driven user experiences.
• Integrate frontend applications with backend AI services.
• Ensure accessibility, usability, and performance optimization.

Cloud & DevOps

• Deploy applications and models in cloud environments (Azure, AWS, or GCP).
• Implement CI/CD pipelines for application and model deployment.
• Apply infrastructure-as-code (Terraform, ARM, Bicep, etc.).
• Implement monitoring, logging, and alerting.
• Ensure security compliance and enterprise-grade governance.

Architecture & Collaboration

• Participate in solution architecture and design discussions.
• Translate business requirements into technical solutions.
• Collaborate with cross-functional teams (product, security, data, UX).
• Contribute to technical standards, best practices, and code reviews.

Required Qualifications

• 8 years of full stack software engineering experience.
• Hands-on AI/ML implementation in production environments.
• Strong proficiency in: Python (FastAPI, Flask, or Django), JavaScript/TypeScript (React, Angular, or Vue), REST API development
• Experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, or equivalent).
• Experience deploying AI workloads in cloud environments (Azure ML, SageMaker, Vertex AI, etc.).
• Experience with relational and NoSQL databases.
• Strong understanding of software engineering principles and design patterns.
• Experience with Docker and container orchestration (Kubernetes preferred).
• Knowledge of secure coding practices and enterprise security standards.

Preferred Qualifications

• Experience with enterprise AI governance and responsible AI frameworks.
• Experience with MLOps and model monitoring tools.
• Knowledge of distributed systems and event-driven architectures.
• Experience with vector databases and semantic search (if applicable to organization).
• Experience in regulated industries (financial services, healthcare, public sector).
• Experience working in Agile/Scrum teams.

Key Competencies

• Strong problem-solving and analytical skills.
• Ability to translate complex AI concepts into scalable technical solutions.
• Excellent communication and stakeholder engagement skills.
• Ownership mindset with the ability to operate independently.
• Strong attention to performance, security, and maintainability.

Job Title : Senior Data Engineer – Databricks

Experience : 14 to 20 Years

Location : HSR Layout, Bangalore

Work Mode : Hybrid – 3 Days WFO

Shift : 11:30 AM – 07:30 PM IST

Positions : 2

Notice Period : Immediate Joiners Only

Interview : 1 Technical Round + 2 Client Rounds

Role Overview :

We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.

The role requires a strong hands-on Data Engineering professional with expertise in Databricks, PySpark, Python, SQL, and AWS, along with technical leadership and stakeholder management experience.

Must-Have Skills :

• 14 to 20 years of Data Engineering experience
• Databricks & Apache Spark / PySpark
• Python & SQL
• AWS Cloud
• Lakehouse Architecture
• ETL / ELT & Distributed Data Processing
• Batch & Streaming Pipelines
• Data Pipeline Optimization & Data Modeling
• CDC & Incremental Processing
• Git, CI/CD & Testing
• Data Quality, Monitoring & Observability
• Technical Leadership & Stakeholder Management

Key Responsibilities :

• Design and build scalable data pipelines using Databricks, PySpark, Python, SQL, and AWS.
• Own data products from design through production.
• Develop batch / streaming pipelines and reusable ETL / ELT frameworks.
• Optimize pipelines for performance, scalability, reliability, and cost.
• Design scalable data architectures and data models.
• Implement data quality, monitoring, lineage, and CI/CD practices.
• Lead technical discussions and mentor engineering teams.
• Collaborate with business stakeholders, architects, product owners, and engineering teams.
• Remain hands-on while providing technical leadership.

Ideal Candidate :

A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.

🔴 Super Urgent : Only Bangalore-based immediate joiners.

About the Company

Fluxsolve Technovations Private Limited (incorporated 2023) builds Fuse-OS — an AI-powered Insurance Distribution Operating System. Fuse-OS is a unified enterprise platform that orchestrates people, processes, and insurance ecosystems across the distribution chain, from lead generation and policy issuance through servicing, reconciliation, payouts, compliance, and business intelligence.

Unlike traditional policy administration tools or point-solution workflow software, Fuse-OS serves insurers, brokers, corporate agents, aggregators, NBFCs, banks, automotive finance companies, OEMs, and dealer networks through three flagship platforms: Insurance Distribution Management, Revenue & Reporting Management, and Embedded & Group Products Management. The platform is cloud-native and AI-native, multi-tenant and modular, with enterprise security controls, configurable business rules, and integration-ready architecture.

About the Founders

Pankaj Sharma — Co-Founder & CEO. IIT Roorkee (B.Tech ECE). Leadership experience across insurance distribution and strategy, including roles at Angel One, Liberty General Insurance, Pasarpolis Indonesia, HDFC ERGO, and Coverfox, along with prior founding experience.

Prenit Wankhede — Co-Founder & CTO. IIT Kanpur (B.Tech + M.Tech EE). Engineering leadership across insurance technology and financial services, including roles at Liberty General Insurance, Morgan Stanley, and Coverfox, along with prior founding experience as CTO.

Role Summary

We are hiring Backend Developers with a full-stack orientation to help build and maintain Fuse-OS. You will primarily work with Python and Django, contribute to APIs and backend services, and comfortably support light frontend work using HTML, JavaScript, jQuery, and CSS. You will learn from senior engineers while delivering reliable features in a multi-tenant SaaS environment.

Key Responsibilities

·      Develop and maintain backend features using Python and Django

·      Build and enhance REST APIs, data models, business logic, and admin tooling

·      Work with relational databases (PostgreSQL) and background job processing patterns

·      Support full-stack contributions using HTML, JavaScript, jQuery, and CSS where needed

·      Write clean, testable code; participate in code reviews and follow team engineering standards

·      Debug issues across application, data, and service layers with guidance from senior engineers

·      Collaborate with frontend, QA, and product/delivery stakeholders on requirements and delivery quality

·      Contribute to technical documentation and knowledge sharing within the team

Required Skills & Qualifications

·      Hands-on experience with Python and Django (academic projects, internships, or professional work)

·      Working knowledge of PostgreSQL / relational data modeling and ORM usage

·      Comfort with Git, Linux basics, and debugging application behavior from logs

·      Frontend familiarity for full-stack contribution: HTML, JavaScript, jQuery, and CSS

·      Ability to read existing codebases, follow established patterns, and deliver incremental improvements

·      Strong analytical problem-solving skills and attention to detail

·      Good written and verbal communication

Preferred / Nice to Have

·      Familiarity with browser automation using Selenium and Python (big plus)

·      Exposure to Celery/Redis, Django REST Framework, or common data-processing libraries

·      Basic AWS familiarity (e.g., compute, storage, monitoring) — optional but good to have

·      Experience with SaaS products, multi-tenant applications, or enterprise web systems

Domain Preference

Familiarity with the insurance industry and InsurTech is preferred but not mandatory. Strong engineering fundamentals and willingness to learn the domain matter more.

What We Offer

·      Opportunity to build a category-defining Insurance Distribution Operating System (Fuse-OS)

·      Work on modern multi-tenant SaaS architecture with meaningful ownership and mentoring

·      Collaborative product and engineering culture focused on quality and customer outcomes

·      Exposure to enterprise SaaS, AI-enabled workflows, and large-scale operational systems

·      Growth path with clear impact on product and customers

Are you interested in writing agentic systems that helps companies like Coca-Cola, ITC and Lenovo drive E-commerce success? Do you want to bring Autonomy to E-commerce? Then read on and apply.

Applied Scientist - Decision AI

Location: Bengaluru

Work Schedule: Hybrid (Candidate must be based in Bengaluru - 1-2 days of WFO may be required at a later date)

About Kily

Kily is an AI company bringing autonomy to digital commerce growth. We build autonomous agents that manage Advertising, Pricing and Listings for brands and sellers across commerce marketplaces.

Performance in modern commerce shifts constantly - across marketplaces, categories and cities - faster than teams can manually track, diagnose and act on. Kily's agents work continuously against real business objectives with each brands unique context, objectives and operating constraints and keeping humans in the loop where it matters.

The Role

We are looking for an Applied Scientist to build the models and decision systems behind Kily's recommendations and actions. The work is grounded in messy, real-world commerce data help build Kily's core decision intelligence layer: systems capable of understanding complex commerce data, determining why performance is changing, deciding what should be done about it, and ultimately taking actions autonomously at scale. You will work at the intersection of learning algorithms, decision making under uncertainty and agentic systems.

What You'll Do

·      Conduct deep analysis of commerce data to derive insights, and identify gaps and new opportunities

·      Develop scalable and effective machine-learning models and optimisation strategies to solve business problems across advertising, pricing and listings

·      Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment

·      Identify and build the sequential feedback loops that make decisions improve over time

·      Design evaluation frameworks to measure the quality and business impact at scale

·      Work closely with engineering, analytics and product teams to take models from experimentation into production

What We're Looking For

·      4+ years in Applied ML/AI, Data Science. Masters or PhD in a quantitative field is a plus

·      Deep proficiency in Python, SQL, statistics and data analysis

·      Hands-on experience developing, deploying and maintaining the end-to-end lifecycle of machine-learning models

·      Experience with LLMs, fine-tuning, AI agents, optimisation or sequential decision systems is a strong plus

·      Exposure to ecommerce, marketplaces, advertising or pricing data is valuable but not essential

·      Strong problem-solving and communication skills; ML research experience is a plus

WHY KILY

Kily is already working with leading brands including ITC, Unilever, Mondelez, Coca-Cola and Lenovo, and has recently raised an INR 30 crore ($3.1 mn) Seed round led by Sorin Investments, with participation from Razorpay and Wyser Capital. You'll have the opportunity to build a foundational AI system from an early stage - one designed not merely to generate insights, but to autonomously drive real-world business

outcomes.

Senior Backend Engineer

What You'll Do :

- Build and scale the core backend and infrastructure powering a customer feedback intelligence platform - owning systems from data ingestion through real-time analytics.

- Harden ML and NLP infrastructure, including pipelines, model serving, and data flows, so features remain reliable in real-world production environments at scale.

- Own critical infrastructure decisions around data models, event flows, and service boundaries, with strong correctness and data-integrity guarantees.

- Instrument systems deeply for observability, ensuring failures surface early and production behavior becomes a source of continuous learning.

- Balance speed, cost, and long-term system health, making pragmatic, cost-effective trade-offs while shipping continuously.

- Partner closely with Product, Design, and the founding team to turn ambiguous problem statements into clear, scalable infrastructure.

- Raise the engineering bar through clean code, thorough design reviews, mentorship, and platform-level improvements.

What It Takes :

- 6-8 years of software engineering experience, with a proven track record of building and shipping reliable systems in production.

- 3+ years at a single organization where you've built infrastructure from the ground up and owned complex projects end to end.

- Deep expertise in infrastructure, including data pipelines, event-driven and microservices architectures, observability, reliability, and cost optimization.

Tech Stack :

-serverless computing, SQL/NoSQL databases, Elasticsearch, or GraphQL.

Bonus :

- Experience building or operating ML/NLP infrastructure such as data pipelines, model serving, feature stores, or inference systems.

Why This Opportunity :

- High Impact : Build foundational backend and infrastructure systems at an early-stage, high-growth technology company.

- Ownership : Take end-to-end responsibility for critical features, systems, and infrastructure.

- Complex Challenges : Work across ML/NLP infrastructure, distributed systems, data pipelines, and real-time analytics.

- Growth : Deepen your technical expertise while having the opportunity to grow into a technical leadership path.

- Culture : Work in an open, collaborative, and values-driven environment with significant autonomy.

- Benefits : Competitive compensation, equity, hybrid work setup, premium healthcare, and more.

CAP-190 : Senior Data Analyst

📍Location : Bangalore / Hyderabad / Chennai / Pune / NCR

🧠Experience : 7 - 15 Years

🆔Job Code : CAP-190

🏢Work Type : Hybrid - 3 Days in a Week

📨Application Link : https://drive.google.com/drive/folders/1bApWyMvoFHvI6krgw9CPbGZHaqYU0kSZ?usp=sharing

Your Experience at a Glance

We’re hiring a Senior Data Analyst for our client (Code Name:CAP) - CAP is a global consulting firm specializing in digital transformation and technology solutions for the financial services industry. As a Data Analyst / Senior Data Analyst at CAP, you will play a pivotal role in delivering actionable insights and supporting data migration initiatives within the financial services domain. You will collaborate with cross-functional teams to define data requirements, ensure data quality, and drive strategic solutions. This senior-level position requires strong technical expertise, stakeholder management, and a proactive approach to delivering change in a dynamic environment.

About the Client (CODE: CAP )

CAP operates at the forefront of the financial services industry, providing consulting, technology, and digital transformation solutions to leading organizations worldwide. With a focus on innovation, CAP empowers clients to navigate complex regulatory landscapes, optimize operations, and drive business growth. The company fosters a collaborative and agile culture, encouraging continuous learning and excellence.

Key Responsibilitie

● Define and obtain source data required to deliver insights and use cases.

● Determine data mapping and join multiple data sets across various sources.

● Develop methods to highlight and report data inconsistencies for user review.

● Propose and assist with suitable data migration sets for stakeholders.

● Support teams in processing data migration sets and coordinating migration activities.

● Plan, track, and coordinate the data migration team and migration run-book.

● Collaborate with stakeholders to avoid negative customer and business impacts.

● Ensure robust communication and escalation mechanisms across project portfolios.

● Implement strategic solutions and avoid short-term workarounds.

● Maintain strong control and compliance standards in data handling.

Required Skills

● Minimum 7+ years of experience as a Data Analyst, preferably in financial services.

● Strong expertise in Pyspark, Python, and SQL.

● Experience with big data programs and data models in banking or financial markets.

● Ability to write SQL queries and navigate databases such as Hive, CMD, Putty, and Note++.

● Excellent analytical skills and commercial acumen.

● Strong verbal and written communication skills.

● Proven ability to manage multiple priorities and deliver within tight deadlines.

● Business analysis skills, including defining and understanding requirements.

● Familiarity with SDLC, Agile processes, and a bias towards TDD.

● Attention to detail and a proactive, problem-solving mindset.

Nice to Have

● Knowledge and experience in Data Quality & Governance.

● Working experience with Spark Scala or Java for Spark.

● Proven track record of managing small, delivery-focused data teams (for senior roles).

● Experience with market data vendors and domains such as Party/Client, Trade, Settlements, Payments, Instrument and Pricing, Market and/or Credit Risk.

Why Join CAP (Code Name)

Join CAP to work on impactful data initiatives within the financial services sector, tackling complex technical challenges and driving meaningful business outcomes. You'll collaborate with talented professionals in a dynamic, agile environment that values

innovation and continuous improvement. CAP offers opportunities for professional growth, skill development, and the chance to contribute to high-visibility projects that shape the future of financial technology.

About the Employment Model

Direct Hire (Client Payroll) : For this role, you’ll be hired directly by the client and be part of their internal team. Straatix supports the hiring process, but your employment, payroll, and benefits are all managed by the client.

Apply here-

https://drive.google.com/drive/folders/1bApWyMvoFHvI6krgw9CPbGZHaqYU0kSZ?usp=sharing

About the Role

You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

Key Responsibilities

• Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
• Design and optimize data models for AI and machine learning workloads.
• Develop reliable data foundations for MLOps, governance, and data lineage.
• Integrate data from multiple sources into modern data platforms.
• Leverage Snowpark ML and Snowflake's native AI capabilities.
• Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

• 3+ years of hands-on experience
• Strong proficiency in SQL and Python.
• Experience with AWS, Azure, or GCP.
• Knowledge of cloud storage services such as S3, ADLS, or GCS.
• Strong understanding of Dimensional Modeling and Data Vault.
• Experience with Scala or Java is a plus.

Tech Stack

• Data Warehouse: Snowflake
• Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
• Cloud: AWS, Azure, GCP
• Storage: S3, ADLS, GCS
• AI/ML: Snowpark ML, MLOps

Perks & Benefits

• Public Speaking & Communication Program
• Mentoring Program with Senior Support Leads
• 360° Progress Reviews
• Weekly Learning Sessions & Guilds
• Paid Certifications
• Hackathons & Innovation Days
• Recognition & Rewards Programs
• Team Socials & Annual Offsites
• Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

Passionate about education? Join us at CK-12 !!

CK-12 (www.ck12.org) is on the lookout for talented, creative, and dedicated people to join our mission to provide great education to students around the world. We are looking for candidates to join our office in Bangalore.

We have a strong education platform that has served over 352+ Million users, have got over 2.88+ Billion questions answered, and have more than 350 thousand customized Flexbooks. We have embarked on an exciting journey to build an AI-powered student tutor and Teacher Assistant to build the next generation of learning platforms.

About CK-12 Foundation

CK-12’s mission is to provide free access to open-source content and technology tools that empower students as well as teachers to enhance and experiment with different learning styles, resources, levels of competence, and circumstances.

To achieve this noble and ambitious vision, we at CK-12 are challenging the traditional model of education to transform it dramatically. Technology has opened up lots of opportunities to revolutionize education for the benefit of students, teachers and parents.

We have chosen to be non-profit so that we can effectively realize our mission and do the right thing! It also provides us with the ability to experiment with big and bold ideas. CK-12 is backed by Vinod Khosla, a renowned technology venture capitalist.

At CK-12, you’ll experience the benefits of working in a dynamic, entrepreneurial, innovative and non-bureaucratic environment where you will get a lot of cool things done than you ever imagined! We are a small group of passionate folks who are determined to disrupt the current form of education.

Technology is key to scale education and we deeply believe in it. Come develop great solutions on our cloud-based (AWS) and AI-first platform delivering rich and interactive content.

Does our mission, people and technologies excite you? If the answer is YES! and you are a great technologist who will challenge status-quo (no order takers please!) by innovating, please come join us! Together, we will change the world!

Check out our latest product offerings

• Introducing Flexi 2.0
• Flexi, our AI-powered Student Tutor – https://www.flexi.org/
• AI-powered Teacher Assistant – https://www.ck12.org/pages/teacher-assistant/

Location: https://goo.gl/maps/NkA2Hr8JhtE3raWr5

Backend Engineer

Basic

● Design, maintain, and monitor infrastructure for data products

● Design and develop RESTful APIs for the data infrastructure

● Design, implement and drive adoption of new analytic technologies and solutions

● Work closely with data scientists, front end engineers and peers to gather requirements and

develop solutions

● Handle and resolve issues escalated from the production operational environment.

● Troubleshoot performance, reliability, and scalability issues.

● Excellent Problem solving skills

● A Code Craftsman that follows best software development and coding practices delivering

understandable and maintainable code with thorough unit tests coverage

Requirements

● 10+ years of development experience with Java, Scala, and/or Python

● Experience with writing and executing queries on RDBMS and NoSQL databases. Working knowledge of MongoDB, MySQL. We are not looking for a DBA.

● Experience with ElasticSearch, OpenSearch, Vector Embeddings, and large-scale search systems.

● Experience designing and operating high-throughput, low-latency backend services in production environments.

● Experience with horizontal and vertical scaling strategies, load balancing, caching, rate

limiting, and performance optimization.

● Experience identifying and resolving application bottlenecks through profiling, monitoring, and performance tuning.

● Experience in virtualization technologies and deployment frameworks (familiarity with working on UNIX shell, Jenkins.)

● Bachelors or masters degree in computer science or equivalent

Desired

● Experience working with FastAPI/Pylons Web Framework.

● Familiarity with messaging and distributed processing systems such as RabbitMQ, Kafka, SQS, or Celery.

● Experience designing systems to support millions of requests, large datasets, and high-concurrency workloads.

● Adept at AI Coding assistants, leveraging them beyond prompting. Working experience in Skill and tool development and usage in AI Coding tools.

● Experience with AWS EC2, Redshift, RDS, S3

Company Overview:

Euphoric Thought Technologies is a technology-driven firm focused on building scalable software solutions for complex enterprise challenges. Operating at the intersection of data-intensive platforms and cloud-native infrastructure, the company partners with global clients to modernize their digital ecosystems. With a culture rooted in engineering excellence and pragmatic problem-solving, Euphoric Thought Technologies empowers its teams to deploy high-impact applications that serve millions of end-users across diverse industry verticals.

Role Overview:

As a Senior Python Developer based in Bangalore, you will serve as a technical anchor for our core product development initiatives. You will work closely with cross-functional teams, including product managers, frontend engineers, and DevOps specialists, to architect robust backend services that drive our platform's performance. Your daily contributions will involve translating complex business requirements into clean, maintainable code, ensuring that our systems remain resilient and efficient as we scale to meet growing user demand.

Key Responsibilities:

- Design and implement high-performance backend services using Python to ensure seamless data processing and system reliability for our enterprise clients.

- Develop and maintain RESTful APIs that facilitate smooth integration between internal microservices and external third-party platforms.

- Optimize database queries and schema designs in SQL to improve application latency and support high-concurrency environments.

- Architect and deploy cloud-native solutions on AWS, ensuring that our infrastructure remains scalable, secure, and cost-effective.

- Implement comprehensive unit and integration testing using PyTest to maintain high code quality and minimize production defects.

- Collaborate with stakeholders to refine technical specifications and mentor junior developers to foster a culture of continuous technical improvement.

Required Skillset:

- Demonstrated expertise in building and scaling production-grade applications using Python, with a deep understanding of Django and Flask frameworks.

- Proven ability to design and document RESTful APIs that adhere to industry standards for security and performance.

- Proficient in managing and optimizing complex SQL databases to support data-heavy application requirements.

- Hands-on experience in configuring and managing AWS services to support deployment pipelines and cloud infrastructure.

- Strong commitment to test-driven development, evidenced by a track record of using PyTest to ensure system stability.

- Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders and work effectively in a collaborative, office-based environment in Bangalore.

- Possess 6 to 9 years of professional software development experience, showcasing a consistent ability to deliver high-quality code in fast-paced environments.

Understand client business requirements and translate them into technical solutions.

Conduct requirement gathering, analysis, solution design, and technical documentation.

Work closely with development, QA, infrastructure, and business teams throughout the project lifecycle.

Provide technical guidance and recommend suitable technologies, architectures, and solutions.

Participate in system integration, implementation, testing, deployment, and troubleshooting.

Analyze existing systems and identify opportunities for optimization and improvement.

Prepare technical specifications, solution documents, architecture diagrams, and project documentation.

Act as a technical point of contact for clients and internal stakeholders.

Identify technical risks, dependencies, and challenges and provide appropriate solutions.

Support pre-sales activities, including technical discussions, solution presentations, and proposal preparation when required.

Stay updated with emerging technologies, industry trends, and best practices.

Strong Software Engineer fullstack profile using NodeJS, Python, and React

2

Mandatory (Experience) - Must have 6+ YOE in Software Development using Python and NodeJS (For backend) & React (For frontend)

3

Mandatory (Core Skills 1): Must have strong experience in working on Typescript

4

Mandatory (Core Skills 2): Must have experience in message based systems like Kafka, RabbitMq, Redis

5

Mandatory (Core Skills 3): Databases - PostgreSQL & NoSQL databases like MongoDB

6

Mandatory (Company) - Product Companies Only

7

Mandatory (Education) - B.Tech or Dual degree (Btech and Mtech or Integrated Msc/MS) from Tier 1 Engineering Institutes (IITs, not NITs). Candidates from other institutions will not be considered unless they come from top-tier product companies

8

Mandatory (Note) : This role is a hybrid role (2 days WFO)

9

Preferred (Experience): Experience in Fin-Tech, Payment, POS and Retail products is highly preferred

10

Preferred (Mentoring): Experience in mentoring, coaching the team.

Job Title

Python Full Stack Developer – AI

Experience: 6-9 Years

Location: Bangalore (Hybrid)

Employment Type: Full-Time

Job Summary

We are seeking a highly skilled Python Full Stack Developer with AI expertise to design, develop, and deploy scalable AI-powered applications. The ideal candidate should have strong experience in Python, Full Stack Development, REST APIs, modern frontend frameworks, and Generative AI technologies, including LLMs, prompt engineering, and AI integrations.

The role involves building end-to-end web applications, integrating AI models, and collaborating with cross-functional teams to deliver innovative AI-driven solutions.

Key Responsibilities

· Design, develop, and maintain scalable full-stack applications using Python.

· Build responsive and interactive user interfaces using React.js, Angular, or Vue.js.

· Develop backend services and RESTful APIs using Django, Flask, or FastAPI.

· Integrate Generative AI models such as OpenAI GPT, Claude, Gemini, or Llama into business applications.

· Develop AI-powered chatbots, assistants, document processing, and workflow automation solutions.

· Implement prompt engineering techniques to optimize AI model performance.

· Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.

· Work with LangChain, LangGraph, or LlamaIndex for LLM orchestration.

· Integrate AI APIs and third-party services into enterprise applications.

· Design and optimize SQL and NoSQL databases.

· Deploy applications on AWS, Azure, or GCP.

· Develop CI/CD pipelines and manage deployments using Docker and Kubernetes.

· Write clean, reusable, and well-documented code following best practices.

· Participate in Agile ceremonies, code reviews, and sprint planning.

Required Technical Skills

Backend

· Python

· Django

· Flask

· FastAPI

Frontend

· React.js / Angular / Vue.js

· HTML5

· CSS3

· JavaScript (ES6+)

· TypeScript

AI / Generative AI

· OpenAI API

· Azure OpenAI

· Gemini API

· Claude API

· Llama Models

· LangChain

Databases

· PostgreSQL

· MySQL

· MongoDB

· Redis

Cloud & DevOps

· AWS / Azure / Google Cloud Platform

· Docker

· Kubernetes

· Git

· GitHub

· Jenkins

· CI/CD

API Development

· REST APIs

· GraphQL (Preferred)

· API Integration

Preferred Skills

· Machine Learning fundamentals

· NLP (Natural Language Processing)

· Hugging Face Transformers

· TensorFlow or PyTorch

· Kafka or RabbitMQ

· Elasticsearch

· Microservices Architecture

· Authentication (OAuth2, JWT)

Qualifications

· Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

· 6–9 years of experience in Python Full Stack Development.

· Hands-on experience with Generative AI and LLM-based application development.

· Experience working in Agile/Scrum environments. 

About the Role

We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.

Key Responsibilities

• Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
• Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
• Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
• Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
• Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
• Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.

Required Skills

• Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
• Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
• Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
• Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
• Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
• Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
• Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
• Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
• Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
• Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.

Nice to Have

• Hands-on exposure to Microsoft Fabric for data integration and analytics.
• Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
• Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
• Domain expertise in financial services.

As a Senior Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems. You will work on optimizing and deploying these models on AWS infrastructure, ensuring scalability and reliability.

Must have skills:

● Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks.

● Python: Good exposure to Python (Pandas, NumPy, FastAPI, advanced Python concepts).

● AWS Bedrock: Hands-on experience with AWS Bedrock and foundation models such as Claude Haiku and Claude Sonnet.

● LLM & GenAI: Hands-on experience in developing RAG pipelines, Prompt Engineering, and LLM-based GenAI applications.

● ML Pipeline Architecture: Experience with Titan Embeddings, Amazon OpenSearch Vector Search, and vector-based retrieval.

● Agentic AI: Hands-on experience with Agentic AI frameworks and AWS Bedrock AgentCore for developing AI agents and workflow orchestration.

● AI Agents & Knowledge Base: Experience developing AI agents for customer query automation and Knowledge Base (KB) solutions.

● Experience with document parsing, chunking, vectorizing and re-ranking strategies.

● Guardrails & Security: Experience configuring AWS Bedrock Guardrails and implementing authentication and authorization for secure AI applications.

● AWS Services: Hands-on experience with API Gateway, Lambda, S3, IAM, CloudWatch, ECR, and SageMaker.

● Software Engineering: Experience with Git, REST APIs, and CI/CD pipelines.

● Relevant AWS certifications (e.g., AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer – Associate, or AWS Certified Solutions Architect – Associate) are a plus.

Good to have skills:

● Hands-on experience with OCR/Document Intelligence engines and NLP techniques for extracting structured information from documents and images.

● Hands-on experience with Bedrock Agentcore

● Hands-on experience with OpenAI, Anthropic, Gemini, or other foundation models.

● Experience with Docker, Kubernetes, and MLOps practices.

● Experience with Redshift, SQL, DynamoDB, or AWS Glue.

● Exposure to model monitoring, evaluation, and observability for GenAI applications.

● Ability to work in an Agile and DevOps environment.

Strong Software Engineer fullstack profile using NodeJS, Python, and React

2

Mandatory (Experience) - Must have 6+ YOE in Software Development using Python and NodeJS (For backend) & React (For frontend)

3

Mandatory (Core Skills 1): Must have strong experience in working on Typescript

4

Mandatory (Core Skills 2): Must have experience in message based systems like Kafka, RabbitMq, Redis

5

Mandatory (Core Skills 3): Databases - PostgreSQL & NoSQL databases like MongoDB

6

Mandatory (Company) - Product Companies Only

7

Mandatory (Education) - B.Tech or Dual degree (Btech and Mtech or Integrated Msc/MS) from Tier 1 Engineering Institutes (IITs, not NITs). Candidates from other institutions will not be considered unless they come from top-tier product companies

8

Mandatory (Note) : This role is a hybrid role (2 days WFO)

9

Preferred (Experience): Experience in Fin-Tech, Payment, POS and Retail products is highly preferred

10

Preferred (Mentoring): Experience in mentoring, coaching the team.

About the Role

We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and AI-assisted software development using Cursor. The role is suited for an engineer who can work directly with clients and internal teams to understand business problems, rapidly build solutions, and take them from prototype to production.

The ideal candidate should have strong expertise in Python, SQL, Databricks, PySpark, data engineering, APIs, and modern AI-assisted development workflows, along with excellent problem-solving and client-facing skills.

Key Responsibilities

Forward Deployed Engineering

• Work directly with clients and stakeholders to understand business and technical requirements.
• Translate business problems into scalable technical and data solutions.
• Rapidly prototype, test, iterate, and productionize solutions.
• Collaborate with engineering, data, AI, and delivery teams to implement customer solutions.
• Troubleshoot production issues and continuously improve deployed solutions.
• Act as a technical bridge between clients and internal engineering teams.

Databricks & Data Engineering

• Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
• Build and optimize ETL/ELT and data processing pipelines.
• Work with Databricks Lakehouse, Delta Lake, Unity Catalog, and Databricks Workflows.
• Develop data ingestion and transformation pipelines for structured and semi-structured data.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.

Cursor & AI-Assisted Development

• Use Cursor and AI-assisted development workflows to accelerate software development, debugging, refactoring, and documentation.
• Effectively use AI coding assistants to understand existing codebases and develop new features.
• Apply appropriate engineering judgment to review, validate, test, and secure AI-generated code.
• Use AI-assisted development for rapid prototyping and proof-of-concept development.
• Work with modern AI/LLM APIs and tools where required for customer solutions.
• Stay current with emerging AI-assisted software engineering practices.

Production & Deployment

• Develop production-ready applications, APIs, and data pipelines.
• Work with Git, CI/CD, APIs, containers, and cloud environments.
• Monitor application and pipeline performance and resolve production issues.
• Ensure solutions meet requirements for scalability, security, reliability, and maintainability.
• Collaborate with Data Scientists and ML Engineers to integrate AI/ML capabilities into production systems.

Required Skills & Experience

• 4+ years of experience in Software Engineering, Data Engineering, AI Engineering, or a related field.
• Strong hands-on experience with Databricks.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Delta Lake and Lakehouse architecture.
• Experience building production-grade data pipelines.
• Hands-on experience with Cursor or similar AI-powered coding assistants.
• Strong understanding of REST APIs and system integrations.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Strong debugging, problem-solving, and analytical skills.
• Excellent communication and client-facing abilities.

Preferred Skills

• Experience with Databricks Unity Catalog, Workflows, and MLflow.
• Experience with Generative AI / LLM applications.
• Knowledge of Claude, OpenAI, Azure OpenAI, or other LLM platforms.
• Experience with RAG, vector databases, embeddings, or AI agents.
• Experience with Docker, Kubernetes, and CI/CD.
• Experience in a consulting, customer-facing engineering, or professional services environment.
• Exposure to Agile/Scrum methodologies.

Key Competencies

• Strong problem-solving and ownership mindset
• Ability to work in ambiguous and fast-paced environments.
• Strong client/stakeholder management skills.
• Ability to understand business requirements and convert them into technical solutions.
• Strong communication and presentation skills.
• Ability to rapidly learn new technologies and tools.
• Comfortable working with AI-assisted development while maintaining high engineering standards.

Education

• Bachelor's or master’s degree in computer science, Information Technology, Engineering, Data Science, or a related discipline.

Role Summary:

We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and Generative AI/Claude to work closely with clients, business stakeholders, and internal engineering teams. The ideal candidate will combine strong Data Engineering, Software Engineering, Databricks, and Generative AI skills with the ability to understand business problems and rapidly build, deploy, and optimize production-ready solutions. This is a client-facing, hands-on engineering role where you will work from problem discovery and solution design through POC development, production deployment, and ongoing optimization.

Key Responsibilities:

Forward Deployed Engineering

• Work directly with clients and stakeholders to understand business and technical requirements.
• Translate business problems into scalable data, AI, and software solutions.
• Design and develop POCs and rapidly validate technical solutions.
• Convert successful POCs into reliable, production-ready applications.
• Work closely with client engineering and data teams during implementation and deployment.
• Troubleshoot production issues and continuously optimize deployed solutions.
• Act as a technical bridge between clients, delivery teams, data engineers, AI engineers, and architects.

Databricks & Data Engineering

• Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
• Build and optimize data ingestion, transformation, and ETL/ELT pipelines.
• Work with Databricks Lakehouse, Delta Lake, and Unity Catalog.
• Develop Databricks Workflows and production data pipelines.
• Implement data processing solutions for structured and semi-structured datasets.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.

Generative AI & Claude

• Build enterprise AI solutions using Claude and other Large Language Models (LLMs).
• Integrate Claude APIs into applications and business workflows.
• Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data.
• Work with embeddings, vector search, semantic search, and knowledge retrieval.
• Develop AI-powered applications for summarization, classification, information extraction, question answering, and document processing.
• Implement prompt engineering, structured outputs, tool/function calling, and context management.
• Develop and integrate AI agents and multi-step AI workflows where applicable.
• Evaluate LLM responses for accuracy, relevance, groundedness, latency, and cost.
• Implement appropriate AI guardrails, security, and data privacy controls.

Production & Deployment

• Deploy AI and data solutions into production environments.
• Work with APIs, microservices, Git, CI/CD, containers, and cloud platforms.
• Monitor application and pipeline performance and troubleshoot issues.
• Collaborate with Data Scientists and ML Engineers to productionize AI/ML models.
• Ensure solutions meet security, scalability, reliability, and maintainability requirements.

Required Skills & Experience

• 4+ years of experience in Data Engineering, Software Engineering, AI/ML Engineering, or a related field.
• Strong hands-on experience with Databricks.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Delta Lake and Lakehouse Architecture.
• Experience working with Generative AI / LLMs.
• Hands-on experience with Claude / Anthropic APIs is preferred.
• Experience with RAG, embeddings, vector databases, and semantic search.
• Strong understanding of REST APIs and enterprise integrations.
• Experience developing production-grade applications and data pipelines.
• Strong problem-solving and troubleshooting capabilities.
• Excellent communication and client-facing skills.

Preferred Skills

• Experience with Claude Code / Anthropic ecosystem.
• Experience with OpenAI, Azure OpenAI, AWS Bedrock, or other LLM platforms.
• Experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
• Experience with Databricks Unity Catalog, Workflows, and MLflow.
• Experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and CI/CD.
• Exposure to AI agents and agentic workflows.
• Knowledge of AI evaluation, guardrails, security, and responsible AI.
• Experience working in consulting, client delivery, or customer-facing engineering environments.

Key Competencies

• Strong customer-facing and stakeholder management skills.
• Ability to understand ambiguous business problems and translate them into technical solutions.
• Strong ownership and execution mindset.
• Ability to rapidly prototype, iterate, and productionize solutions.
• Strong analytical and troubleshooting skills.
• Comfortable working in fast-paced and dynamic client environments.
• Excellent written and verbal communication.
• Ability to work independently as well as collaboratively with distributed teams.

Strong hands-on experience with Adobe Workfront.

Workfront configuration and administration.

Workflows, approval processes, templates, queues, reports, and dashboards.

Custom Forms and Custom Fields.

Strong understanding of Workfront data model and project/work management processes.

Hands-on experience with Workfront Fusion.

Experience with REST APIs, webhooks, JSON, HTTP methods, and integrations.

Experience integrating Workfront with third-party enterprise applications.

Knowledge of automation and iPaaS concepts.

Good understanding of data mapping, transformations, error handling, and integration monitoring.

Knowledge of JavaScript or scripting is an advantage.

Role Overview

We are looking for experienced Azure Databricks Data Engineers with strong hands-on expertise in Apache Spark/PySpark, Python, SQL, and Azure Data Factory (ADF). The candidate will be responsible for designing, developing, and optimizing scalable data engineering solutions on the Azure cloud platform.

Mandatory Skills

• Strong hands-on experience with Azure Databricks
• Strong knowledge of Apache Spark and/or PySpark
• Proficiency in Python
• Strong SQL development and query optimization skills
• Hands-on experience with Azure Data Factory (ADF)
• Experience developing and maintaining scalable ETL/ELT data pipelines
• Good understanding of Azure data engineering concepts and cloud-based data platforms

Key Responsibilities

• Design, develop, and maintain data pipelines using Azure Databricks and ADF
• Develop efficient data processing solutions using PySpark/Spark and Python
• Write complex SQL queries for data transformation, validation, and analysis
• Build scalable ETL/ELT workflows for large datasets
• Optimize Spark jobs, Databricks notebooks, and data pipelines for performance
• Integrate data from multiple sources into Azure-based data platforms
• Implement data quality, validation, error handling, and monitoring mechanisms
• Troubleshoot production issues and provide timely resolutions
• Collaborate with data architects, analysts, developers, and business stakeholders
• Follow best practices for code quality, security, performance, and maintainability

Experience Requirements

For 5+ Years

• 5+ years of overall experience in data engineering
• Strong hands-on experience in Azure Databricks, PySpark/Spark, Python, SQL, and ADF
• Experience working on enterprise-scale data pipelines

For 9+ Years

• 9+ years of overall experience in data engineering
• Strong expertise in Azure Databricks and modern Azure data engineering
• Proven experience designing and optimizing large-scale data pipelines
• Ability to lead technical discussions and mentor junior engineers

Preferred Skills

• Azure Data Lake Storage (ADLS)
• Delta Lake
• Databricks Workflows
• Azure DevOps / CI-CD
• Git
• Data warehousing concepts
• Experience with Agile/Scrum methodologies

What you'll do

The Software Engineer will serve as a full stack developer within the AI and Automation team, focusing on building AI agents, chatbots, and automation solutions. The role involves taking ownership and accountability to meet commitments, developing software using programming languages, and designing, executing, and reporting on system and service tests to ensure applications function as required. Additional responsibilities include monitoring, diagnosing, and resolving technology issues, as well as supporting team members by carrying out prescribed design activities using established procedures.

What you'll bring

3+ years of experience in full stack application development using Python (for backend) and JavaScript/Typescript (for frontend).

Strong understanding of Java.

Strong understanding of Machine Learning /MLOps using Python .

Familiarity with Agentic AI frameworks.

Familiarity with Kubernetes (K8S) and Docker.

Experience in developing solutions using Azure storage and compute solutions.

Proven experience working with Azure AI solutions, especially AI Foundry and AI Search.

Experience in developing distributed event-driven applications using brokers such as Apache Kafka, IBM MQ, Solace, or Azure Event Hub.

Proven experience in working with DevOps frameworks, GIT, and CI/CD pipelines.

Experience developing integrations using established Enterprise Application Integration patterns and tools such as Apache Camel.

Required Qualifications

Specify the minimum educational qualifications necessary for this role, including degree type, field of study, and level attained.

Applicants should hold a bachelor’s degree in any discipline and possess practical experience in software development. Degrees in Computer Science, Software Engineering, or Information Technology are particularly advantageous. 

About the Role

We are looking for a motivated Data Engineer with 2+ years of professional experience to join our team. You will be responsible for designing, developing, and maintaining scalable data pipelines and cloud-based data solutions while taking ownership across the full software development lifecycle.

The ideal candidate will have strong experience in modern data engineering practices, cloud platforms, and marketing/advertising data integrations such as Google Ads, Meta Ads, and analytics platforms.

This role is suited for someone who enjoys solving complex data challenges, building reliable systems, and working in a fast-paced environment.

Key Responsibilities

• Design, build, and maintain scalable and reliable ETL/ELT data pipelines.
• Develop and optimize data models, transformations, and warehouse solutions for analytics and reporting.
• Work with marketing and advertising datasets from platforms such as Google Ads, Meta Ads, Google Analytics, and similar ecosystems.
• Integrate APIs, third-party systems, and cloud-native services into data workflows.
• Optimize complex SQL queries and improve pipeline performance and reliability.
• Implement data quality checks, monitoring, and observability across pipelines.
• Collaborate with cross-functional teams including product, analytics, and engineering teams to deliver data-driven solutions.
• Contribute to software engineering best practices including Git workflows, CI/CD pipelines, testing, and documentation.
• Participate in architecture discussions and help improve data platform standards and best practices.
• Build and maintain solutions within Google Cloud Platform (GCP) environments.

Qualifications

• 2+ years of professional experience in Data Engineering or related fields.
• Strong proficiency in Python programming.
• Advanced SQL skills with experience in query optimization and data warehousing concepts.
• Experience working with marketing and advertising platforms such as Google Ads, Meta Ads, Google Analytics, DV360, or similar platforms.
• Experience working with AI-assisted coding and development tools such as Claude Code, Cursor, or similar platforms
• Hands-on experience leveraging AI-based development tools to accelerate data engineering implementation and automation
• Familiarity with AI-powered coding assistants and agentic development workflows
• Understanding of marketing data pipelines, attribution reporting, campaign analytics, or customer analytics is highly desirable.
• Hands-on experience with at least one major data engineering technology such as Airflow, Spark, Kafka, Databricks, or similar frameworks.
• Strong experience with Google Cloud Platform (GCP) services such as BigQuery, Cloud Run, Cloud Functions, GCS, or Composer.
• Familiarity with APIs, Linux environments, CLI tools, Git, and CI/CD workflows.
• Strong understanding of data pipeline design, orchestration, monitoring, and troubleshooting.
• Excellent communication, collaboration, and problem-solving skills.
• Ability to work independently and contribute across multiple technical domains.

Who are we?

Inflexion Analytics is a team of data science and analytics consultants based in London, UK, and Bangalore India. Founded in 2015, we have built a strong track record and foundation serving demanding clients. We are now looking to achieve significant growth and become a leading specialist consultancy in the data science field.

What we do?

We help businesses to improve performance through better insight and decision-making. To achieve this, we offer services across the data science value chain including; data strategy, data engineering, data insights, and visual analytics. We work with a global client base, including clients based in the US, UK, Europe, and Australia. 

Position: Computer Vision Engineer

Experience: 2–3 Years

Location: Bengaluru, Karnataka

Employment Type: Full-time

About the Role

We are seeking a highly motivated Computer Vision Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating computer vision models and algorithms and pipelines for UAVs operating in both GNSS-available and GNSS-denied environments.

The ideal candidate should have a strong foundation in theory of deep learning and machine learning, strong understanding of electromagnetic spectrum, imaging fundamentals, camera principles, and mathematical concepts with hands-on experience in implementing these algorithms on embedded or real-time systems.

Key Responsibilities

• Design, develop, and optimise AI Models
• Make custom CNNs/ modify existing CNNs to suit specific problems at hand
• Handle end-to-end training flow
• Implement end to end inference pipelines on standard PCs as well as on embedded systems
• Understand performance benchmarks and assess the accuracy and inference times
• Implement traditional image processing algorithms
• Factor the code to leverage underlying hardware architecture
• Prune the networks for efficiency
• Integrate the system within the application framework using C++
• Work closely with perception, controls, embedded software, and systems engineering teams.

Required Qualifications

• B.E./B.Tech/M.E./M.Tech in Computer Science and Engineering, Electronics, ECE, Mechatronics, or a related discipline.
• 2–3 years of experience in relevant area
• Strong understanding of: Linear Algebra, Probability and Statistics, AI-ML-DL fundamentals, Image processing, Camera Functioning
• Strong programming skills in C++ and Python.
• Experience with MATLAB for algorithm development and validation.
• Familiarity with Linux development environments.
• Experience with Git version control.

Preferred Skills

• Experience with Camera, IMU Calibration and Synchronisation
• Experience with multi-sensor fusion.
• Experience working with NVIDIA devices
• Experience on FPGA will be an added advantage
• Full understanding of Git functionality
• Exposure to airborne software development processes and coding standards (e.g., MISRA C++).

Personal Attributes

• Strong analytical and problem-solving skills.
• Ability to work independently on challenging technical problems.
• Good communication and documentation skills.
• Passion for solving challenging problems
• Willingness to participate in field trials and flight testing.
• Team playwe

 Job Description:

• Job title : Senior DevOps Engineer (On-Premises Automation)        
• Experience: 8+ years
• Location: Chennai / Pune / Hyderabad / Bangalore
• Shift: UK Shift
• Work Mode: Onsite (WFO)

Roles and Responsibilities:

• This engagement automates end-to-end infrastructure build provisioning across on-prem and Azure. The team will build a shared ServiceNow-led intake, approval, orchestration, and closed-loop status model, using Jenkins/Ansible for on-prem builds and Azure DevOps/Terraform for cloud builds. Automation includes standards, security/compliance controls, scan gates, CMDB/change updates, and handover.              

Key Responsibilities:

• Lead secure and repeatable on-prem build provisioning pipelines
• Lead Jenkins CI/CD for automated on-prem provisioning and configuration.
• Create pipeline templates for VM/physical host, OS deployment, configuration, certification, and rollback.
• Embed hardened-image validation, scan gates, secrets handling, approvals, and audit evidence.
• Lead Ansible roles, PowerShell modules, test automation, and code reviews.
• Implement logging, monitoring, and root-cause analysis; support UAT and hypercare.       

Required Qualifications:

• 8–10 years in DevOps, platform engineering, or infrastructure automation.
• Bachelor’s degree or equivalent experience.
• Jenkins
• Git, CI/CD
• Ansible, PowerShell
• Python, IaC
• security scanning, secrets management
• Windows/Linux.

Job Summary

We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.

Technical Skills

• Strong hands-on experience in Python and PySpark development.
• Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
• Experience with Power BI Data Modeling and Semantic Layer development.
• Proficiency in DAX (Data Analysis Expressions).
• Experience designing and managing Semantic Models in Power BI.
• Strong SQL skills and experience working with large datasets.
• Knowledge of data warehousing concepts and best practices.

Preferred Skills

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Exposure to modern data platforms like Databricks.
• Understanding of data governance and data quality frameworks.

Company Description

Appiness Interactive Pvt. Ltd. is a Bangalore-based product development and UX firm that

specializes in digital services for startups to fortune-500s. We work closely with our clients to

create a comprehensive soul for their brand in the online world, engaged through multiple

platforms of digital media. Our team is young, passionate, and aggressive, not afraid to think

out of the box or tread the un-trodden path in order to deliver the best results for our clients.

We pride ourselves on Practical Creativity where the idea is only as good as the returns it

fetches for our clients.

About the Role

You will own the reliability of the distributed data systems, the streaming runtime and

processing engines that move hundreds of billions of rows per day for top-tier enterprises. This

is an SRE role for our big data stack: Kafka, Spark, Flink, Ray, Redis, and data warehouses, all

running on Kubernetes.

This is not a cloud-provisioning role. We are looking for someone who has lived inside stateful,

high-throughput systems in production who has chased down a broker outage, a checkpoint

stall, a crashlooping cache, and a sink that silently stopped writing, and who fixes the

architecture rather than the symptom. If keeping a large, busy data platform alive and fast is the

kind of problem you find satisfying, you will have a lot of fun working with us. This is a unique

opportunity to shape the foundation of a product that is defining the next wave of intelligent,

context-aware data movement.

Responsibilities

● Streaming & Data Plane Reliability: Own the health of our Kafka-based runtime

(managed via Strimzi on Kubernetes) - broker health, topic lifecycle and count

management, partition and throughput tuning, certificate/secret rotation, and version

upgrades - at a scale of hundreds of thousands of topics and hundreds of billions of rows

per day.

● Distributed Processing Engines: Operate and tune distributed system workloads in

production in collaboration with backend teams, resource allocation, autoscaling,

checkpointing, backpressure, and failure recovery for both batch and streaming jobs.

● Stateful Services: Run Redis clusters and other stateful systems reliably - failover,

persistence, liveness/readiness tuning, and capacity planning under heavy and bursty

load.

● Kubernetes & Operators: Take end-to-end ownership of Amazon EKS, Google GKE and

the operators (Strimzi and others) running our stateful data workloads - cluster lifecycle,

scaling, version upgrades, and resource governance.

● Observability: Build deep, data-aware monitoring - consumer lag, throughput, partition

skew, job latency, error rates - not just host and CPU metrics. Make the data plane's

behavior legible before it breaks.

● Incident Management: Lead root-cause analysis for distributed-systems failures (broker

outages, crashloops, sink decommissions, control-plane race conditions) and drive

durable fixes. Mitigate fast, but design out the recurrence.

● Infrastructure as Code & Automation: Provision and manage cloud infrastructure with

Terraform; build operational runbooks and automation, including for air-gapped/private

enterprise installs (pre-staged images, operator-facing procedures).

● Collaboration: Partner with platform, runtime, and connector engineering - and with

SREs and support - to ship and scale new data-movement features reliably in a

large-scale Linux environment.

Qualifications

● Experience: 6+ years in infrastructure, SRE, or DevOps, with significant time spent

operating production distributed data systems (not just application/cloud infra).

● Kafka: Deep, hands-on operational experience running Kafka at scale in production -

ideally on Kubernetes via Strimzi - including upgrades, topic/partition management,

performance tuning, and TLS/secret rotation.

● Distributed Processing (Strong Plus): Production experience operating one or more of

Spark, Flink, or Ray - resource tuning, checkpointing, failure recovery.

● Stateful Systems (Must Have): Production experience with Redis (clustering, persistence,

failover) and a solid understanding of operating stateful workloads on Kubernetes

(StatefulSets, PVCs, probes, operators).

● Data Warehouses: Familiarity operating against Snowflake, BigQuery, or similar, and an

understanding of JDBC connectivity and sink reliability.

● Kubernetes & EKS: Strong hands-on EKS cluster creation, scaling, version upgrades, and

operator management.

● Infrastructure as Code: Advanced proficiency with Terraform.

● Programming: Proficiency in Python (or similar) for automation and tooling. Comfort

reading and debugging JVM-based systems is a strong plus.

● Reliability Mindset: Demonstrated ownership of incident management, RCA, capacity

planning, and performance tuning for high-throughput systems.

● CI/CD: Solid understanding of CI/CD methodology (Jenkins, GitHub Actions, or GitLab CI)

for containerized and non-containerized apps. Supporting, not the core of the role.

● Nice to Have: Configuration management (Ansible preferred); broader AWS services

(IAM, VPC, EC2, S3, Lambda); AWS CloudFormation.

● Soft Skills: Excellent communication and organizational skills; ability to coordinate

effectively within a team and with customers.

Why This Might Be Worth It

● You own the hard part. The stateful, distributed systems that move billions of rows are

the platform's most demanding reliability problems - and they'd be yours.

● Impact at scale from day one. Your work keeps mission-critical data flowing for

companies like DoorDash and LinkedIn.

● The AI wave is real for us. We're not bolting AI onto a legacy product. Intelligent

connectors, context-aware data movement, and agentic workflows are the core of what

we're building next - on top of the runtime you'd run. ○ Small team, big problems. Direct

access to the CTO, real influence over product direction, and the autonomy to make

significant technical bets. ○ Recognized platform, startup energy. Enterprise validation

with the speed and ownership of an early-stage company.

Role Summary

Seeking an experienced SQL Developer with strong expertise in Data Lake architecture, Data Engineering, AI/ML data modelling, and Vector Database design. The candidate will be responsible for building scalable data platforms, developing optimized SQL solutions, designing AI-ready data models, and supporting enterprise analytics and GenAI initiatives.

Key Responsibilities

• Design, develop, and optimize complex SQL queries, stored procedures, views, and database objects.
• Build, maintain, and govern enterprise Data Lakes for structured, semi-structured, and unstructured data.
• Design scalable data models for Analytics, Machine Learning (ML), and AI applications.
• Develop and maintain data ingestion, transformation, and data preparation pipelines.
• Architect and manage Vector Database solutions supporting GenAI, semantic search, embeddings, and RAG-based applications.
• Ensure data quality, security, performance, governance, and scalability across platforms.
• Integrate data from multiple enterprise systems, databases, APIs, and business applications.
• Collaborate with Business, Analytics, Data Science, and AI teams to deliver enterprise data solutions.

Mandatory Skills

• Advanced SQL Development (SQL Server, PostgreSQL, Oracle, MySQL, etc.)
• Data Lake Architecture, Development, and Maintenance
• Data Warehousing & Dimensional Data Modelling
• AI/ML Data Modelling and Feature Engineering
• Python for Data Engineering, Data Processing, and Automation
• Query Performance Tuning & Database Optimization
• Data Governance & Data Quality Management
• Vector Database Architecture and Management (Pinecone, Qdrant, Weaviate, Milvus, Chroma, or similar)
• Experience handling large-scale structured and unstructured datasets

Preferred Skills

• Experience with GenAI, RAG (Retrieval-Augmented Generation), Embeddings, and LLM-based applications
• PySpark and Distributed Data Processing
• Power BI or Enterprise Reporting Platforms
• Knowledge of MLOps, AI data pipelines, and modern data architectures

Key Attributes

• Strong analytical and problem-solving skills
• Ability to independently own end-to-end data platform solutions
• Excellent communication and stakeholder management skills
• Passion for Data Engineering, AI, ML, and GenAI technologies

Ideal Candidate

A hands-on SQL Developer who can build and maintain enterprise Data Lakes, design AI/ML-ready data models, develop Python-based data solutions, and architect Vector Database platforms to support advanced analytics, AI, and GenAI initiatives.

Job Title: Automation Engineer – Watermelon Tool 

Experience: 6–7 Years

Location: Bangalore

Work Mode: Hybrid

Notice Period: Immediate Joiners (Apply only if you can join within 15 Days)

Key Responsibilities:

Design, develop, and maintain automated test scripts using the Watermelon automation tool.

Build and enhance automation frameworks for web, API, and enterprise applications.

Analyze business and functional requirements to identify automation opportunities.

Execute automated regression, smoke, sanity, and functional test suites.

Maintain reusable automation components and improve test coverage.

Integrate automation scripts with CI/CD pipelines.

Perform root cause analysis for failed test cases and provide detailed defect reports.

Work closely with developers, business analysts, and QA teams to resolve issues.

Ensure automation standards, coding best practices, and documentation are followed.

Participate in Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.

Required Skills:

5–10 years of experience in Automation Testing.

Strong hands-on experience with the Watermelon automation tool (mandatory).

Experience in test automation framework development and maintenance.

Knowledge of API testing and automation.

Experience with SQL for database validation.

Familiarity with Git or other version control systems.

Experience with CI/CD tools such as Jenkins, Azure DevOps, or GitLab CI.

Strong understanding of SDLC, STLC, and Agile methodologies.

Excellent debugging, analytical, and problem-solving skills.

Good verbal and written communication skills.

Preferred Skills:

Experience with Selenium, Playwright, Cypress, or similar automation tools.

Knowledge of Java, Python, or JavaScript for automation scripting.

Exposure to cloud platforms such as AWS, Azure, or GCP.

Experience working in enterprise-scale automation projects.

ISTQB or equivalent testing certification is an added advantage.

Roles & Responsibilities:

Develop scalable and maintainable automation solutions.

Improve automation coverage and reduce manual testing effort.

Collaborate with stakeholders to deliver quality software releases.

Identify automation improvements and implement best practices.

Support production validation and release testing activities.

Mandatory Skills:

Watermelon Automation Tool

Test Automation

Automation Framework Development

API Testing

SQL

Git

CI/CD

Agile Methodology

Generative AI Engineer 

Role Overview:

You will be responsible for the hands-on development, coding, and deployment of AI-powered features. Your focus is on writing clean, efficient code to integrate LLMs into our existing tech stack, building robust data pipelines for RAG, and ensuring the reliability of model outputs through rigorous testing and optimization.

Key Responsibilities

• Application Implementation: Code and integrate LLM APIs (OpenAI, Anthropic, etc.) or local models into backend services using Python, FastAPI, etc.,
• MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript) to expose internal databases, APIs, and file systems to AI agents.
• RAG Implementation: Build and maintain the "plumbing" for Retrieval-Augmented Generation—specifically coding the data ingestion scripts, text chunking logic, and metadata filtering.
• Vector DB Management: Perform day-to-day operations on vector databases (Pinecone, Milvus, etc.), including indexing, querying, and optimizing search retrieval.
• Prompt Programming: Develop, version-control, and refine complex prompt templates (using Jinja2 or similar) to ensure consistent structured outputs (JSON/YAML).
• Agent Development: Implement multi-step workflows using LangChain, LangGraph, CrewAI etc.,, focusing on tool-calling logic and error handling.
• Evaluation & Testing: Build automated test suites to detect "hallucinations" and measure accuracy using frameworks.
• Performance Tuning: Implement caching layers and streaming responses to reduce latency and improve the end-user experience; Token optimization.
• Data Pre-processing: Clean and tokenize datasets for model fine-tuning or high-quality context retrieval.

Technical Skills (The "Execution" Stack)

• Language: Advanced Python (Asyncio, Pydantic) and optional TypeScript/Node.js (for full-stack integration).
• AI Frameworks: Hands-on experience with any of LangChain, LlamaIndex, and Hugging Face Transformers. RAG and Vector search concepts.
• Data Handling: Proficiency in SQL and handling unstructured data formats (PDFs, Markdown, JSON).
• Deployment: Practical experience with Docker, GitHub Actions (CI/CD), and experience with OpenTelemetry, LangSmith, Weights & Biases etc., Understanding of evaluation/guardrails.
• MCP/API Proficiency: Deep understanding of RESTful APIs, Streaming HTTP, MCP server vs client, JSONRPC

Job Title : MLOps Engineer

Mode: Hybrid

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary:

We are looking for a skilled and proactive ML Engineer with strong expertise in Python, Databricks, and Machine Learning model development. The ideal candidate should be proficient in building scalable data pipelines and deploying ML models, with a working knowledge of MLOps principles and tooling. This role offers an opportunity to work on impactful AI/ML initiatives in a collaborative environment.

Key Responsibilities:

• Develop and maintain machine learning pipelines for training, testing, and deploying models

• Design and implement infrastructure for managing and monitoring machine learning models

• Work with data scientists to build scalable, efficient, and automated model training and testing processes

• Collaborate with software engineers to integrate machine learning models into production systems

• Automate and optimize the deployment and scaling of machine learning models in a distributed computing environment

• Monitor and troubleshoot machine learning systems and infrastructure to ensure high availability and performance

• Develop and maintain documentation and best practices for MLOps processes and procedures.

Experience:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

• 3+ years of experience in MLOps or related field, including building and deploying machine learning models at scale

•Proficiency in programming languages such as Python, Java, and C++

•Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras

• Experience with containerization technologies such as Docker and Kubernetes

• Strong understanding of DevOps principles and practices

• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud

Job Description:

We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and Python programming.

You will work closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models and integrate generative AI solutions into existing workflows.

Your responsibilities will include:

• Collaborating with cross-functional teams to design and deliver high-performance AI models, including NLP, computer vision, semantics engines, linguistic analysis, risk management, and time-series prediction models. Integrating generative AI solutions into existing workflow systems.
• Developing and maintaining the ML Operations CI/CD pipeline for seamless deployment and monitoring. Training, tuning, and optimizing AI models and algorithms for enhanced performance.
• Implementing complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.
• Creating ML/AI models for business teams and establishing metrics to track their accuracy and performance. Overseeing the full lifecycle of algorithm development, from ideation to deployment and monitoring. Evaluating and ranking ML algorithms based on their potential success in solving specific problems.
• Serving as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.

Required Experience and Skills:

Machine Learning:

• Proficient in generative AI techniques, prompt engineering, and Retrieval-Augmented Generation (RAG) (3+ years).
• Experience with Large Language Models (LLMs) such as OpenAI, Gemini, LLAMA, and other state-of-the-art models (3+ years).
• Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow, Keras, BERT, LayoutLM, and traditional ML algorithms (5+ years).
• Experience with distributed ML/AI training libraries/models: Koalas, Horovod, DDP.

Python Programming and Software Engineering:

• Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (5+ years).
• Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).
• Proficient in software design concepts focusing on cohesion and coupling (2+ years). Knowledge of SOLID principles (2+ years).

Education and Experience:

• Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.
• At least 5 years of experience as a software engineer and 5 years of ML-related programming.

Job Description:

Position: Senior Data Engineer

Location: Chennai / Pune / Bangalore / Hyderabad

Working Type: WFO

Shift: UK Shift (2:00 – 11:00 PM)

Experience : 7+ years overall

Interviews: Assessment || 2 Interview rounds.

Notice Period: Immediate Joiner

Key Responsibilities

Implement ingestion, transformation, and optimization of enterprise data sources into Microsoft Fabric Lakehouse environments.

Configure and optimize Fivetran connectors (Oracle, SQL DB, etc.)

Manage large-volume ingestion and backfill operations

Implement Bronze to Silver transformation pipelines

Develop incremental load and CDC logic

Optimize Lakehouse performance and storage patterns

Implement monitoring (record counts, load duration, failure tracking)

Support Dev/Test/Prod promotion processes

Required Qualifications

7+ years of data engineering experience

Hands-on experience with Microsoft Fabric or Azure Synapse/Data Factory

Strong experience with Fivetran or similar ELT tools

Experience handling high-volume datasets (hundreds of millions of records)

Proficiency in SQL, Python, and data modeling concepts

Strong understanding of Medallion architecture.

Strong Azure Databricks Engineer / Senior Data Engineer Profile

2

Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3

Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4

Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5

Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6

Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7

Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8

Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9

Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10

Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

Roles & Responsibilities

• Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration

of enterprise-wide data from diverse sources

• Build and optimize data engineering workflows using Databricks and PySpark

• Write efficient, high-performance SQL for data transformation and analysis

• Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing,

data models, and pipelines

• Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the

development lifecycle

• Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production

environments with proper change control processes

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions

• Ensure data quality, reliability, and performance across all pipelines and platforms

Ideal Candidate

1Strong Azure Databricks Engineer / Senior Data Engineer Profile

2Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

Experience: 4–6 Years

Domain: Automotive IoT | Connected Vehicles | Firmware & OTA

Core Stack: Rust | AWS | IoT Core | Apache Kafka | MemoryDB

Key Responsibilities  

OTA & Firmware Lifecycle  

• Co-own OTA firmware rollout operations across multi-ECU connected vehicle architectures.
• Design automated mechanisms to detect update failures, network interruptions, verification errors, and stalled deployments.
• Implement deterministic retry, recovery, and rollback mechanisms to ensure reliable firmware updates without vehicle bricking.
• Ensure firmware package integrity, signature validation, and data security throughout the OTA pipeline.

Data Engineering & Telemetry  

• Design and maintain real-time streaming pipelines for vehicle telemetry, heartbeats, OTA campaign status, and ECU state changes.
• Build high-throughput data services and workers using Rust for payload routing, processing, and verification.
• Use Apache Kafka and AWS IoT Core for real-time data ingestion and event streaming.
• Leverage AWS MemoryDB for Redis for low-latency fleet state, campaign progression, and session management.
• Build resilient pipelines capable of handling intermittent connectivity, noisy networks, and out-of-order data.

Monitoring & Analytics  

• Build real-time dashboards for fleet health, firmware versions, OTA campaigns, and update progress.
• Define and monitor key OTA metrics including success/failure rates, retry rates, failure categories, and completion time.
• Implement automated alerting and anomaly detection for unexpected failure spikes during staged or canary rollouts.
• Analyze logs, traces, and telemetry data to identify campaign bottlenecks, telemetry loss, and hardware-related failures.

Required Skills  

Mandatory  

• 4–6 years of experience in Data Engineering, Software Engineering, or IoT Backend Engineering.
• Strong hands-on experience with Rust for backend/data processing applications.
• Experience with AWS, particularly IoT Core, S3, ECS/EKS, and Lambda.
• Strong experience with Apache Kafka and real-time data pipelines.
• Hands-on experience with AWS MemoryDB for Redis or Redis Enterprise.
• Working knowledge of Python and SQL.
• Experience with MQTT, WebSockets, and HTTP/S protocols.
• Strong understanding of distributed systems, streaming data, and resilient data pipelines.

Preferred  

• Experience with firmware lifecycle management and OTA systems.
• Exposure to connected vehicles, automotive IoT, telemetry platforms, or connected hardware fleets.
• Experience with device shadows and fleet/device state management.
• Experience building telemetry dashboards using Power BI, Apache Superset, or custom dashboards.
• Experience with staged/canary deployments and automated failure recovery.

Primary Technology Stack  

• Languages: Rust, Python, SQL
• Cloud: AWS, IoT Core, S3, ECS/EKS, Lambda
• Streaming: Apache Kafka
• Caching & State: AWS MemoryDB for Redis, Redis
• IoT Protocols: MQTT, WebSockets, HTTP/S
• Analytics & Visualization: Power BI, Apache Superset
• Domain: Automotive IoT, Vehicle Telemetry, OTA, Firmware Management