Software Engineer

Job Description: Lead - Cloud Engineering (AWS / Azure)

Role Title: Lead - Cloud Engineering

Experience Level: 10+ Years

Domain Focus: Healthcare AI & Cloud Infrastructure

Location: Remote

Job Overview

We are seeking an experienced Lead - Cloud Engineering with over 10 years of IT experience to lead our cloud strategy, architecture, and infrastructure teams. In this role, you will oversee end-to-end cloud deployment, multi-cloud migration, and scalable architecture designed to support cutting-edge Generative AI applications in the healthcare technology domain.

The ideal candidate brings deep technical expertise in both AWS and Azure, strong hands-on capability in cloud infrastructure, and proven leadership experience driving security, compliance, and team growth.

Key Responsibilities

Cloud Architecture & Migration

• Lead the architecture, design, and execution of cloud migrations, deployments, and modernizations across AWS and Azure environments.
• Drive Infrastructure as Code (IaC) standards using Terraform, CloudFormation, or Bicep to ensure scalable, automated infrastructure provisioning.
• Build high-availability, low-latency architectures optimized for data-intensive Generative AI and Machine Learning workloads.

Security & Healthcare Compliance

• Enforce healthcare security standards including HIPAA, HITRUST, SOC 2, and data governance best practices across all cloud assets.
• Implement Zero-Trust security, Identity Access Management (IAM), data encryption key management, and continuous vulnerability monitoring.

Leadership & Team Management

• Manage, mentor, and scale a high-performing team of DevOps, Cloud, and SRE Engineers.
• Drive Agile workflows, sprint planning, incident response frameworks, and SLA compliance.
• Collaborate closely with Data Engineering, AI/ML, and Software Product teams to align infrastructure with business roadmaps.

Operations & FinOps

• Establish cloud cost optimization strategies (FinOps) to manage computing costs associated with AI models and large-scale data processing.
• Manage monitoring, alerting, and telemetry frameworks (e.g., Prometheus, Datadog, CloudWatch) to ensure 99.99% uptime.

Key Requirements

• Experience: 10+ years of overall IT experience with at least 5+ years in a cloud leadership or lead architect role.
• Cloud Platforms: Advanced hands-on expertise with both AWS (e.g., EC2, S3, EKS, Bedrock, SageMaker) and Azure (e.g., AKS, Azure OpenAI, Blob, Virtual Machines).
• DevOps & IaC: Strong background in Terraform, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
• Domain Knowledge: Prior experience building or managing cloud environments within Healthcare, Life Sciences, or HealthTech is strongly preferred.
• AI/ML Familiarity: Experience supporting cloud infrastructure for machine learning pipelines, LLM deployments, or GPU compute management.
• Certifications (Preferred): AWS Certified Solutions Architect – Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).

About the Role

We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.

This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.

This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions — not people management or process.

Responsibilities

• Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
• Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
• Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
• Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
• Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
• Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
• Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
• Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.

Qualifications

• Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
• Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
• Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
• Advanced knowledge of Kubernetes and Terraform in production environments.
• Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
• Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
• Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
• Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
• Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
• Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
• Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
• Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Our Culture

Who we are:

Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.

How we work:

• We move Blitzy Fast: Time is both our company’s and our clients’ most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
• Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
• Passion for Invention: We’re pushing the frontier of what’s possible, requiring constant innovation and iteration.
• We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
• We believe in being ‘everyday athletes’: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for 

Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

• Own the overall product architecture and technical roadmap.
• Design and build scalable, secure, and highly available enterprise applications.
• Lead the design and implementation of new product features from concept to production.
• Remain hands-on with coding and contribute to critical product components.
• Drive architecture reviews, code quality, performance optimization, and engineering best practices.
• Lead cloud architecture, security, scalability, and DevOps initiatives.
• Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
• Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

• 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
• Strong hands-on expertise in Python and modern backend frameworks.
• Deep experience with AWS services and cloud-native application architecture.
• Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
• Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
• Strong knowledge of SQL and NoSQL databases.
• Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
• Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
• Strong analytical, problem-solving, and decision-making skills.

AWS / Kubernetes / OpenShift / Linux –

Location: Bangalore

Experience: 7–10 Years

Mandatory Skills:

• Strong hands-on experience with AWS
• Experience in Kubernetes & OpenShift
• Strong knowledge of Linux administration
• Experience with Docker & containerization
• Knowledge of CI/CD pipelines and DevOps practices
• Troubleshooting, monitoring, and deployment experience

Role: Cloud/DevOps Engineer – AWS, Kubernetes & OpenShift

Tasks & Responsibilities: (Major task and role person will have to perform – list all the relevant points)    

Together with the Business Cloud Services team, you will design, deploy, and operate a cloud‑native Kubernetes PaaS platform on Azure, ensuring high availability, security, and operational excellence.

Your main duties include:

·      Drive cloud‑native automation and self‑service capabilities, ensuring platform security, availability, and disaster recovery readiness

·      Design, operate, and continuously improve Kubernetes clusters and PaaS environments on Azure / AKS

·      Collaborate closely with development teams on deployment strategies, operational requirements, and platform integration

·      Review and maintain infrastructure‑as‑code configurations, CI/CD pipelines, and cloud‑native deployments

·      Build and maintain CI/CD pipelines using Azure DevOps

·      Implement and operate infrastructure‑as‑code solutions using Terraform, Helm, and Ansible

·      Manage containerized workloads and orchestration across cloud‑native environments

·      Set up, operate, and enhance monitoring, logging, and alerting stacks using tools such as Prometheus and Grafana

·      Coordinate with support teams on platform incidents, escalations, and post‑incident analysis

·      Contribute to incident response, continuous improvement, and operational stability

·      Support the development and refinement of DevOps practices, runbooks, and operational standards

·      Actively contributes to improving developer experience and platform reliability

Education & Trainings + Certifications: (Basic & Professional)

·      Bachelor’s degree (Preferably engineering graduate)

·      Azure Solutions Architect Expert Certification is a plus.

·      (optional) ITIL Foundation 

Technical know-how: (Mention the technology on which person must be experienced)

Mandatory

o  Bachelor’s degree in computer science, Information Systems, or a related field

o  5+ years of relevant professional experience in DevOps, Cloud Engineering, or Platform Engineering roles

o  Strong Linux system administration skills for operating production‑grade cloud‑native platforms

o  Proven experience with Microsoft Azure, including AKS and Azure DevOps tooling

o  Strong expertise in Kubernetes, including cluster operations, RBAC, networking, and storage

o  Hands‑on experience with container technologies such as Docker and container registries

o  Proficiency with Terraform, Helm, Ansible, and PowerShell

o  Experience building and operating CI/CD pipelines using Azure DevOps or equivalent tools

o  Cloud‑native monitoring and observability experience using Prometheus, Grafana, and alerting pipelines

o  Solid understanding of security and compliance requirements such as PCI DSS and SOC2

o  Scripting skills for automation and tooling (Bash, Python, PowerShell)

o  Practical experience using Git for version control

o  Excellent communication skills in English (Spanish is a plus)

o  Automation‑first mindset and strong collaboration skills within Agile teams

Good to know

Principles of Agile Software Development.

·      GitHub Actions, GitLab CI, Jenkins, Azure DevOps

·      Containers: Docker, Kubernetes (EKS / AKS / GKE)

·      Configuration Management: Ansible

The Data People Shaping Tomorrow | Your Career, Accelerated

You’ve got the skills. The curiosity. The hunger to grow, try new things and make a real impact. We’re a growing global tech consultancy. Some of the world's biggest businesses turn to us to help bring their data, AI, cloud and digital solutions to life.

We’re the home base for talented technologists who want more and are looking to take their career to the next level by having more learning, more variety, more support and more chances to do meaningful work. If that sounds like the kind of place you’d thrive in, keep reading.

What You’ll Do

●GCP Architecture & Infrastructure: Design, build, and maintain scalable enterprise cloud infrastructure within Google Cloud Platform (GCP 2.0), ensuring high availability and adherence to cloud governance best practices.

●Automation & IaC Excellence: Develop, manage, and automate infrastructure deployments at scale using Terraform as Infrastructure as Code (IaC).

●CI/CD Infrastructure & Tooling: Build, optimize, and support robust CI/CD infrastructure and pipelines using GitLab to streamline provisioning, configuration, and code delivery.

●Cloud Networking & Enterprise Security: Implement and maintain enterprise cloud networking solutions, secure cross-cloud connectivity, and cloud security configurations to safeguard platform operations.

●Operations & Change Governance: Support platform services and enterprise cloud operations, driving troubleshooting, incident resolution, and performance tuning across complex cloud and hybrid environments.

●Technical Leadership & Mentoring: Act as a cloud infrastructure Subject Matter Expert (SME), collaborating with platform engineering, networking, and application teams while mentoring junior engineers.

●Strategic Integrations & Stakeholder Management: Support connectivity and seamless integrations for enterprise core systems (including SAP environments), translating technical cloud architectures into clear, actionable outcomes for business and technical stakeholders.

What We Are Looking For

● 6+ years of high-impact engineering experience architecting, building, and operating enterprise cloud infrastructure on Google Cloud Platform (GCP).

●Deep proficiency in Infrastructure as Code (IaC) using Terraform for automated infrastructure provisioning and lifecycle management.

●Advanced technical expertise with GitLab, including CI/CD pipeline design, optimization, and repository management.

●Strong foundation in cloud networking and security, including VPC design, enterprise connectivity, routing, and identity management.

●Proven track record in enterprise cloud operations, automation, and infrastructure troubleshooting across complex environments.

●Experience supporting core enterprise integrations, such as SAP or large-scale enterprise applications on cloud platforms.

●Outstanding communication skills with a proven ability to collaborate across platform teams and influence technical and business stakeholders[cite: 2].

What You’ll Get

Your work matters—and so do you. That’s why we back your skills with a structure that supports

your development, celebrates your wins, and helps you keep growing - professionally and

personally.

Growth & Development

●Accelerate your career: Lead delivery across diverse industries and cutting-edge technologies to expand your leadership mindset.

●Access global brands: Engage directly with world-leading businesses and manage relationships at the executive level.

●Proprietary frameworks & accelerators: Use our playbooks and toolkits to fast-track meaningful work and project outcomes.

●Paid Certifications: Stay ahead with certifications across ITIL, PMP, and all major cloud platforms.

Culture & Rewards

●Supportive Leadership: Benefit from senior mentoring and clear pathways into practice leadership or account management.

●360° Progress Reviews: Honest, developmental feedback to fuel your professional growth.

●Guilds & Weekly Training: Learn from peers in communities focused on data, AI, and delivery excellence.

●Hackathons & Innovation Days: Challenge yourself to build cool stuff beyond business as usual.

●Kudos & Recognition: Great work doesn’t go unnoticed, supported by impact-based rewards and incentives.

●Articulate: Master executive communication through our specialized public speaking program.

●Employee Assistance Program: Full-spectrum support for your medical, mental, and personal wellbeing.

●Real Connection: From Friday socials to team-building days, we genuinely enjoy the ride together.

Final Word

If you’re looking for the place where your growth will go into overdrive, where you’ll work with

great humans, get access to cutting-edge tools and genuinely enjoy the ride?

Senior Cloud Site Reliability Engineer (CSRE) – Azure

About Searce:

Searce is an AI-native, engineering-led modern technology consultancy that empowers

clients to futurify their businesses by delivering real, intelligent business outcomes. As a

trusted partner for over 3,000 clients globally, Searce specializes in cloud modernization,

data engineering, applied AI, and robust cloud platform security. Driven by a "HAPPIER"

cultural mindset and our proprietary evlos problem-solving framework, we eliminate

bureaucratic fluff to build working prototypes fast and scale enterprise production

environments intelligently. We don't just fix systems; we leverage multi-cloud technologies

to transform client operations into distinct competitive advantages.

Position Overview:

We are looking for a high-caliber Senior or Lead Cloud Site Reliability Engineer (CSRE) to

architect, secure, and stabilize next-generation hybrid and multi-cloud environments.

Operating at the intersection of infrastructure design, security compliance, and production

operations, you will serve as the technical Subject Matter Expert (SME) across GCP, Azure,

and AWS.

Whether optimizing a microservice mesh on GKE, tuning autoscaling on AKS, or driving a

massive disaster recovery drill across AWS regions, your focus will be absolute reliability. For

the Lead path, you will couple this deep engineering toolkit with stakeholder management

and mentorship to drive an elite operational culture.

Experience & Level Expectation:

Years of Experience: 3 to 10 years of intensive, hands-on production operations

experience in a dedicated DevOps, Cloud Platform Engineering, or SRE role.

Associate level (3-5 Years): Expected to show flawless execution of IaC, advanced

triaging of infrastructure failures, and ownership of the CI/CD and deployment

lifecycles.

Intermediate level (5-10 Years): Expected to take architectural ownership, serve as

primary Incident Commander for complex outages, design cross-cloud governance

frameworks, and act as a reliable bridge between technical teams and client

leadership.

Key Responsibilities & Role Expectations:

Multi-Cloud Platforms & Orchestration: Design, configure, and maintain

production-grade Kubernetes clusters across major platforms (AKS).

Manage advanced network routing, service meshes (e.g., Istio), and multi-tenant

isolation.

Infrastructure as Code (IaC) & GitOps: Build declarative, enterprise-grade, reusable

infrastructure components using Terraform or Crossplane. Standardize automated

environment provisioning to eliminate configuration drift across multi-branch

environments.

Incident Management & Reliability (SRE): Own and optimize the production on-call

rotation. Lead rapid mitigation strategies for Sev-1/Sev-2 system outages, reducing

Mean Time to Recovery (MTTR) through centralized log and metric correlation.

Root Cause Analysis (RCA): Facilitate rigorous, blameless post-incident reviews to

identify core architectural vulnerabilities and establish long-term fixes preventing

recurrence.

Lifecycle, Patching & Upgrades: Plan and execute zero-downtime cluster upgrades,

operating system patching strategies (Linux/Windows), database lifecycle updates,

and multi-region Disaster Recovery (DR) failover drills.

Core Core Operations & Legacy Integration: Manage enterprise-level hybrid

networking architecture (VPCs, Firewalls, Load Balancers, DNS routing, and DHCP

configurations) while effectively connecting cloud native services to legacy

infrastructures like Active Directory.

Security & Governance: Embed Zero Trust policies, secure secrets management

(Secrets Manager/Key Vault), and continuous vulnerability patching into the

automated SDLC pipeline.

Required Technical Skills:

- Microsoft Azure: Azure Virtual Machines, Virtual Networks, Azure Active Directory, Azure Update Management.

- Containers & Orchestration

• Production-level management of GKE, AKS, and EKS.
• Advanced mastery of Docker, Helm, Kubernetes StatefulSets, Pod Disruption

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)

● 10–15 years of overall experience in backend engineering, with strong exposure to

Python and/or Golang.

● 3–5 years of experience managing engineering teams.

● Proven experience delivering large-scale, distributed systems in production

environments.

● Strong understanding of microservices, cloud-native architecture, and DevOps

practices.

● Hands-on background in backend engineering (able to guide teams technically, even

if not coding daily).

● Familiarity with CI/CD pipelines, observability, and performance optimization.

● Experience in financial services or high-transaction domains is a plus.

● Experience leading teams that have utilized AI-driven development practices (e.g.,

agentic coding, LLM integration) to improve productivity and innovation is a

significant advantage.

Skills

● Excellent leadership and people management abilities.

● Strong communication and stakeholder management skills.

● Ability to balance technical depth with business priorities.

● Problem-solving mindset with a focus on delivery and impact.

● Passion for building engineering culture and improving developer experience.

1. Company Description:

Tatvic, is a marketing analytics company focusing on generating insights from data using long association with Google & its infrastructure. We breed,recognize and reward performance. As a company we are growing very fast & we are under transformation. To enable this transformation we need future leaders with eyesight which balances execution & strategic understanding.

Website: www.tatvic.com

2. Role Details

• Role: Lead Data Engineer
• Band: L4
• Department: Data Engineering
• Reporting to: L5 / Head of Delivery
• Location: Ahmedabad
• Job Type: Full Time
• Experience: 6-8 years of relevant experience
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.

3. Mission & Role Overview

• Mission: To create high-level organizational impact by leading a team to design and deliver scalable, high-performance cloud-native data solutions. The Lead Data Engineer (L4) is responsible for ensuring technical excellence—specifically in BigQuery optimization and secure GCP/AWS architectures—while driving the transition to Agentic AI workflows and creating value through the development of L1-L3 engineers.
• Role Overview: This is a pivotal leadership role on the Management Track, responsible for end-to-end data outcomes for the function. The Lead Engineer ensures the quality of engineering execution, manages team utilization and resource allocation, and serves as the primary technical representative in cross-functional forums with Marketing, Strategy, and Product teams.

4. Key Responsibilities

• Lead the design, development, and deployment of scalable and efficient cloud-based data pipelines and architectures.
• Build reusable data solutions and software components that serve multiple customers and use cases.
• Architect cloud environments using GCP, ensuring best practices in IAM, Security, and Networking.
• Conduct Exploratory Data Analysis (EDA) on clickstream and behavioral datasets to derive insights.
• Manage end-to-end ETL processes, including data extraction, transformation, and loading using Python, SQL, and Airflow.
• Design and build production-grade software (APIs, services, internal tools) with sound engineering practices — version control, testing, CI/CD, and code review.
• Extend data platforms with AI capabilities — integrating LLMs, RAG pipelines, and agentic workflows where they add clear business value.
• Perform Root Cause Analysis (RCA) and resolve data quality, pipeline, or application issues.
• Collaborate cross-functionally with Marketing, Insights, Product, and Engineering teams to align data initiatives with business goals.
• Document architectures, design decisions, and operations clearly and consistently.
• Coach and mentor team members, ensuring technical excellence and continuous learning.
• Participate in recruitment and knowledge-sharing through interviews, blogs, and webinars.

5. Must-Have & Good-to-Have Skills

Must-Have Skills:

• Strong understanding of clickstream data and data pipeline architecture
• Hands-on experience with cloud platforms (GCP)
• Expertise in SQL, Python, and Airflow
• Solid software engineering foundation — API design, testing, version control, and deployment practices
• Proven ability to perform exploratory data analysis and data validation
• Knowledge of cloud security, IAM, and networking best practices
• Working knowledge of building or integrating AI/LLM-based components into existing systems
• Excellent problem-solving, stakeholder management, and communication skills

Good-to-Have Skills:

• Certifications such as: Google Cloud Professional Data Engineer / Cloud Architect
• AWS Certified Data Analytics or Azure Data Engineer Associate
• Google Analytics 4 (GAIQ)
• Experience in marketing attribution, commerce data, or analytics ecosystems
• Exposure to cost optimization and cloud resource management
• Experience with agent frameworks (LangChain, ADK, MCP) or LLM APIs
• Experience building automation frameworks or internal data tools

6. Not-a-Fit Criteria

• Individual Contributor Focus: Operates as the team's best individual contributor instead of building team capability or empowering L3s.
• Information Hoarding: Keeps architectural patterns or tribal knowledge trapped in their head rather than creating reusable playbooks and documentation.
• Avoidance of Conflict: Avoids difficult performance conversations with underperforming team members, allowing capability gaps to persist.
• Activity Over Outcomes: Measures success by "tasks completed" rather than pipeline stability, data accuracy, or business impact.
• Functional Siloing: Fails to build partnerships with Marketing or Product teams, leading to misaligned data delivery.

Our Culture & Perks - Where Passion Meets Purpose:

• Competitive CTC: Based on experience and skillset
• Medical Insurance for you and your family
• Return-to-Work Program for New Moms — because career breaks shouldn’t break momentum
• 1 Work From Home Day/Month — flexibility when life calls
• 2 Birthday Leaves/Year — one for you, one for someone you love
• Monthly Engagement Activities — from game nights to learning sessions
• Inclusive Culture & Equal Opportunity Employer — diversity drives our innovation
• We Think Like Engineers & Athletes: we build, we iterate, we scale, we win — together
• 5-day workweek — because balance drives brilliance

Experience - 4 to 6 year

Location – Ahmedabad/Pune/Indore

• Additional Job Description

Additional Job Description

Required Skills and Experience: 

• Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
• Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
• Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
• Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
• Demonstrated experience implementing content filtering / moderation systems.
• Solid skills working with structured and unstructured data and advanced feature engineering.
• Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
• Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
• Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
• Good knowledge of security, data governance, and privacy best practices for AI systems.