50+ Remote Python Jobs in India

Role: Senior Engineer (Cloud Cost Optimization Engineer – Azure FinOps)

Employment Type: Permanent with VDart Digital

Work Location: Remote

Project Description -

Identify and implement cost optimization opportunities across Azure, Databricks, Snowflake, Power BI, and enterprise data platforms.

Drive resource rightsizing, utilization improvements, and governance initiatives.

Build automation, monitoring, and proactive cost controls.

Implement FinOps best practices, cost allocation models, and optimization guardrails.

Partner with engineering and business teams to deliver sustainable cloud savings.

Develop dashboards, reporting, and executive insights on cloud spend and optimization opportunities.

Agentic AI Automation for all the above use cases

Key Skills

• Cloud Cost Optimization & FinOps

• Azure Cost Management

• Databricks Optimization (Photon, Spot Instances, Auto-Termination)

• Snowflake Warehouse & Storage Optimization

• Power BI Capacity Optimization

• Python / PowerShell Automation

• Terraform / Infrastructure as Code

• Azure DevOps & CI/CD

• Resource Rightsizing & Capacity Planning

• Cost Governance, Azure Policy & RBAC

• Cost Analytics, Reporting & Forecasting

Preferred Experience

• 5+ years of experience in Cloud Engineering, Platform Engineering, FinOps, DevOps, or Infrastructure Optimization.

• Hands-on experience with Azure and enterprise-scale cloud environments.

• Proven track record of delivering measurable cloud cost savings and optimization outcomes.

About ZYSYGY

ZYSYGY is building Germany's zero-fee payment network. Merchants pay zero transaction fees. We route payments directly over SEPA Instant, bypassing Visa, Mastercard, and the entire card network chain. No hardware. No card reader. Just a phone.

We are building the first company to combine a fully software-based merchant POS with a consumer super-app for everyday financial life: payments, transport, utilities, government services, all in one place. Think what UPI did for India. We are doing it for Germany, from the ground up, on banking rails.

Role Overview

You will join the core engineering team as a founding engineer. You will own the backend payment engine end to end: transaction flows, wallet management, SEPA Instant settlement, KYB/KYC integration, recurring mandates, refund logic, and the compliance export layer (DATEV, Kassenbuch, GoBD, fiskaltrust). On mobile, you will contribute to the React Native consumer and merchant apps alongside our mobile engineer.

You will own what you build from development through deployment, monitoring, and production reliability. The architecture decisions you make in the first six months will run in production for years.

What you will do

Design and build the backend payment engine: transaction flows, wallet management, SEPA Instant settlement, offline payment authorization, and recurring mandate billing.

Own KYB/KYC integration and the compliance export layer: DATEV, Kassenbuch, GoBD, and fiskaltrust for KassenSichV.

Build REST APIs for financial-grade reliability and high-throughput transaction processing, including full R-transaction handling and reconciliation pipelines.

Contribute to the React Native consumer and merchant mobile apps alongside our mobile engineer.

Own the full lifecycle of what you build, from development through deployment, monitoring, and continuous improvement.

Integrate AI tooling into your development workflow as a matter of course: code generation, automated testing, and intelligent review.

Who you are

Meaningful hands-on experience building payment systems, fintech infrastructure, or financial APIs.

You have designed a ledger. You understand double-entry bookkeeping, immutable transaction records, and why you never update a financial row.

You have solved the partial failure. Money left one wallet and did not arrive in the other. You know how to detect it, resolve it, and make sure it does not happen again.

You understand idempotency at a design level. You have built systems that survive client retries, duplicate webhooks, and network drops without double-charging anyone.

You have built or reasoned about reconciliation: detecting discrepancies between your internal ledger and an external settlement file, and resolving them reliably at scale.

You understand KYC and KYB state machines, what happens when verification status changes mid-transaction, and what a regulator expects from your audit trail.

You are comfortable with SQL databases and own the full lifecycle of your code from development through deployment.

You can communicate technical decisions clearly to non-technical stakeholders. At this stage of the company, that matters.

You are a continuous learner. Payments infrastructure is a deep domain and you treat it that way.

You are comfortable with ambiguity and early-stage risk. There is no playbook yet. You will help write it.

Strong academic background preferred. Demonstrated engineering ability matters more than institution.

Relocation

Relocation to Munich, Germany, is on the table for the right candidate, including visa support.

Connect with the Founder

You can also connect with me on LinkedIn at www.linkedin.com/in/shabbir-maimoon

Job Title : AI Agent / Agentic Engineer

Experience : 4+ Years

Employment Type : Contract

Role Level : Mid–Senior

Project : Leading South Africa Telecommunications Operator

Department : Data & AI Engineering

Job Overview :

We are looking for an experienced AI Agent / Agentic Engineer to design, develop, and deploy intelligent AI agents that automate business workflows and enhance data-driven decision-making.

The ideal candidate will have hands-on experience building autonomous or semi-autonomous AI systems using modern agent frameworks, integrating enterprise APIs, and deploying production-ready agentic solutions with strong safety and governance practices.

Mandatory Skills :

Python, AI Agents, LangGraph, CrewAI, AutoGen, Semantic Kernel, Multi-Agent Systems, Tool Calling, REST APIs, LLMs, RAG, Prompt Engineering, Agent Guardrails, Azure OpenAI (Preferred).

Key Responsibilities :

• Design and develop AI agents for workflow automation and business analytics.
• Build multi-step reasoning, planning, and tool-calling workflows using modern agent frameworks.
• Integrate AI agents with enterprise APIs, databases, and business applications.
• Implement agent guardrails, permission controls, human-in-the-loop workflows, and monitoring.
• Collaborate with GenAI, API, MLOps, and Data Engineering teams to deliver scalable AI solutions.
• Optimize agent performance, reliability, latency, and operational cost.
• Document AI agent capabilities, limitations, and deployment processes.

Required Skills :

• 4+ years of experience in Software Engineering or AI Engineering.
• Strong programming skills in Python.
• Hands-on experience with AI agent frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Experience building autonomous or semi-autonomous AI agents with multi-step reasoning and tool calling.
• Experience integrating AI solutions with REST APIs, enterprise systems, and data platforms.
• Understanding of LLMs, RAG concepts, prompt engineering, and AI agent orchestration.
• Knowledge of AI safety, guardrails, monitoring, and human-in-the-loop workflows.
• Experience deploying production-ready AI applications.

Good to Have :

• Experience with Azure OpenAI, Azure AI Foundry, or Azure AI Agent Service.
• Exposure to telecom, analytics, or enterprise AI solutions.
• Knowledge of cloud platforms, MLOps, and AI deployment best practices.

AI Developer - Only immediate joiner

7+yrs of Experience

C2C Opportunity

• Hands-on experience building LLM-based applications.
• Experience with LangGraph, LangChain, Semantic Kernel, or similar orchestration frameworks.
• Strong Python development experience.
• intent routing

o state management

o tool calling

o workflow orchestration

o fallback handling

o human-in-the-loop flows

• Experience integrating with REST APIs.
• Experience with Azure OpenAI, Azure AI Foundry, OpenAI APIs, or similar model platforms.
• Understanding of prompt design, prompt versioning, and prompt testing.
• Basic understanding of authentication, secure API calls, and data privacy.
• Experience with logging, tracing, or monitoring LLM applications.
• Ability to work with architects and backend teams to convert business workflows into executable agent flows.

Role: Full Stack GEN AI Engineer

Location: Remote - Bengaluru

Duration: Fulltime With VDart Digital

The role demands a developer who is not just familiar with Large Language Models (LLMs), but is an expert in building autonomous agentic workflows using the modern GenAI stack (LangChain, CrewAI, Vector DBs). Expertise in system design, cloud-native technologies, and CI/CD for AI-driven applications is essential for this high-impact delivery role.

Responsibilities

·        Design, develop, and maintain full-stack applications that are scalable, robust, and meet the company's quality standards, with a specific focus on Generative AI integration.

·        Agentic Orchestration: Build and deploy sophisticated multi-agent systems and autonomous workflows using frameworks like LangChain, CrewAI, or LangGraph.

·        Collaborate effectively with cross-functional teams to define, design, and ship new features that bridge the gap between raw AI power and intuitive user workflows.

·        Exhibit strong problem-solving skills with an emphasis on product development and driving architecture choices that enable a world-class user experience.

·        Utilize a variety of modern web technologies and frameworks (React.js, Angular, or Vue.js) to build responsive and accessible user interfaces.

·        Develop and maintain RESTful APIs and services with optimal performance and scalability, handling streaming AI responses and complex function-calling logic.

·        Ensure code quality, organization, and automatization through best practices, including unit tests for prompts, model evaluation pipelines, and automated CI/CD for AI-driven features.

·        Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using Vector Databases and advanced retrieval techniques.

·        Adapt to emerging technologies and frameworks, specifically new GenAI tools and frontier models, and apply them to operational and business needs.

·        Manage individual project priorities, deadlines, and deliverables with minimal supervision.

Skill Requirements

·        Excellent oral and written communication skills, with the ability to articulate complex AI and technical ideas to both technical and non-technical audiences.

·        Profound knowledge of application development, data structures, networking, operating systems, and DBMS.

·        Strong proficiency in backend programming languages for API development such as Python, Java, JavaScript (Node.js), or Go.

·        Expertise in front-end technologies and frameworks such as React.js, Angular, or Vue.js.

·        GenAI & Agentic Tools: Deep hands-on experience with LangChain, CrewAI, or AutoGen. Ability to manage agent memory, state, and tool-calling.

·        In-depth understanding of SQL/NoSQL databases, data modeling, and experience with Vector Databases for RAG implementations.

·        Solid grasp of system design, microservices architecture, and cloud-native technologies including Docker, Kubernetes, and GitHub Actions.

·        Experience with distributed computing, machine learning frameworks, and tools, with a primary focus on Generative AI.

·        Desirable (Good to Have): Experience with Generative or Adaptive UI development, where the interface dynamically adapts or renders components based on LLM outputs and real-time AI reasoning.

·        A strong desire to learn and master new technologies and techniques in the rapidly evolving GenAI landscape.

Qualifications

·        Bachelor’s degree in Computer Science, Engineering, or a related field.

·        A minimum of 3-5 years of experience in full-stack development, with a proven track record of building and deploying Generative AI applications and agents.

·        A portfolio of successfully deployed web applications and services, specifically showcasing AI agents, RAG implementations, or complex AI-driven features.

Role overview:

We are hiring one Senior Backend Engineer to take end-to-end ownership of our serverless backend — a hands-on IC role for someone both technically excellent and comfortable being one of the few people the entire backend depends on. You'll own the services across several Node.js and Python repositories, work directly with the founders and product team, and set the technical bar for reliability, security, and performance.

Key responsibilities

• Design, build, and operate AWS Lambda services across our HCM/workforce, project-management, commercial/revenue, permissions, and document domains — each comprising dozens of functions.
• Own the multi-tenant PostgreSQL data layer — schema design, query performance, and the permission/relationship model — end to end.
• Maintain and evolve the request path — API Gateway → custom Lambda authorizer → VPC-bound Lambda → private databases — including the runtime IAM/credential model that scopes every request.
• Safeguard tenant isolation and security across a per-company Cognito authentication model.
• Build and maintain integrations with external construction data environments (Asite, Autodesk Construction Cloud), including large-scale document synchronization.
• Optimize performance and reliability to keep latency-sensitive endpoints well within platform limits under growing load.
• Raise the engineering bar — testing, observability, CI/CD, and modernization of legacy components.
• Debug and resolve production incidents to root cause, and put safeguards in place so they don't recur.
• Document decisions and designs and collaborate with the frontend (Angular) and product teams.

Challenges you'll solve.

We prefer to be candid — these are the problems that make this role genuinely interesting:

Latency under a hard ceiling

API Gateway terminates any request beyond ~29 seconds regardless of the Lambda's own timeout — yet much of our value comes from heavy cross-project reporting. You'll keep p95 latency within budget through set-based SQL, pagination, streaming, and asynchronous processing.

Least-privilege, per-request security

A shared custom authorizer mints short-lived, request-scoped credentials via sts:AssumeRole under a strict 2,048-character inline session-policy limit. You'll design permission models that stay within that budget and reason about IAM precisely.

Graph-shaped data, relational store

The permission and relationship model is inherently graph-like, but lives in PostgreSQL — you'll model it with recursive queries, careful indexing, and set-based traversal rather than reaching for a separate graph engine.

Watertight multi-tenancy

One Cognito pool per company and tenant-scoped access throughout — isolation is a first-order concern.

VPC-bound serverless

Lambdas run inside a VPC to reach private databases; you'll manage cold starts, connection lifecycles, and pool limits.

Resilient external integrations

Syncing large document sets from third-party APIs (including SOAP/XML) demands backpressure, deduplication, retries, and graceful partial-failure handling.

Compute-heavy workloads

Server-side PDF generation, image processing, and multi-currency handling within Lambda's memory and time constraints.

The stack.

Runtime — Node.js, Python, AWS Lambda

AWS services — -1 API Gateway, Lambda, Cognito, STS / IAM, Secrets Manager, S3 CloudWatch, VPC, EC2

Infrastructure & CI/CD- AWS SAM, CodePipeline → CodeBuild Shared Data —PostgreSQL

Qualifications.

• 5+ years building and operating production backend systems.
• Deep expertise in Node.js and JavaScript — the asynchronous model, event loop, and memory behavior — plus solid working proficiency in Python and its production behavior.
• Strong hands-on AWS experience, ideally serverless (Lambda, API Gateway, IAM/STS, VPC, Secrets Manager, CloudWatch) — able to reason about IAM policies, not just apply them.
• Advanced SQL and relational data modeling — set-based query design and a working understanding of why N+1 patterns cause production issues.
• Proven production-debugging ability — root-cause analysis in distributed systems from logs and first principles.
• Strong ownership, sound judgment, and clear written communication — able to make good decisions with incomplete information and explain trade-offs to non-engineers.

Interview Process:

Introductory call-Mutual fit and role overview.

Technical deep-dive- A walkthrough of a challenging production problem you have owned.

Practical exercise -A realistic backend task, or a walkthrough of your own representative code.

System design- Collaborative design on a real scenario.

Final conversation- Values, ownership, compensation, and offer.

The problem you are solving

250 million students sit exams in India every year. Every answer sheet is graded by a tired human with a red pen, in a room with no AC, in 45-degree heat, under political pressure. The variance in marks between two evaluators on the same paper can be 15-20%. That is not education. That is luck. We are building the AI that changes this — reading handwriting, understanding context, scoring semantically, flagging uncertainty, matching faculty-level accuracy. We need the engineer who will make this work at scale.

What you will build

HTR

Handwriting recognition on smudged, mixed-script answer sheets — not clean printed text

Layout

Detect question boundaries, diagrams, tables, margin notes across 20+ page booklets

NLP

Semantic scoring — does this answer mean the right thing, not just contain the right words

Confidence

Know when the model is unsure and route to human review with explainability

Scale

Process millions of pages during exam seasons — async pipeline on AWS SQS + GPU workers

Must have built something hard — any of these

Document OCR / HTR pipeline

Fine-tuned LLM for domain scoring

Layout / document understanding model

Semantic similarity / NLI at scale

GPU inference pipeline (TensorRT/ONNX)

Multi-language NLP (Indic languages +)

Competition — 3 rounds

Round 1

Given 50 real (anonymized) answer sheets: build a pipeline that extracts, structures and scores them. Accuracy vs faculty marks is the metric.

Round 2

48-hour sprint: improve your Round 1 model given live feedback on failure cases. Confidence calibration included.

Round 3

Live oral defense with Sachin and Hemant. Walk us through every architectural decision. We will break it.

The problem you are solving

50,000 students. Hundreds of classrooms. Attendance marked on paper by a faculty member who has 90 seconds to call roll before lecture starts. It is inaccurate, gameable, and meaningless as data. We are replacing it with existing CCTV infrastructure — no new hardware, no wristbands, no apps. Just cameras that already exist, a model that recognises faces at scale in real-time, and a system smart enough to also tell you which rooms are overcrowded, which are empty, which have lights burning with nobody inside, and which need security attention. Campus intelligence, from cameras that are already there.

What you will build

Face recog.

Identify 50,000 enrolled students from CCTV feed — low-res, partial occlusion, varying angles

Attendance

Real-time auto-marking at scale, synced to the student ERP — no manual input

Crowd detects

Flag overcrowded rooms vs capacity threshold, real-time alerts to admin

Empty rooms

Detect booked-but-empty rooms and free them up automatically

Utilities

Lights on in empty room, fan running, AC on — flag for facilities team with camera snapshot

Edge + cloud

Low-latency processing at edge where needed, aggregation and analytics on cloud

Must have built something hard — any of these

Face recognition at 10,000+ identities

Real-time video analytics pipeline

YOLO / object detection production deploys

Multi-camera synchronization system

Edge inference (Jetson / Open VINO / ONNX)

Crowd / occupancy detection system

Competition — 3 rounds

Round 1

Given a set of low-res CCTV stills from a real campus: identify occupied vs empty rooms, count heads, detect lights-on-no-occupancy. Submit working code.

Round 2

48-hour sprint: extend your solution to handle a 10-camera simulated feed simultaneously. Latency under 2 seconds per frame is the bar.

Round 3

Live oral defense with Sachin and Hemant. Scale it to 500 cameras. Where does it break? How do you fix it?

Job Title : Python Backend Developer

Experience : 3 to 6 Years / 6 to 8 Years

Location : Remote

Shift : US Shift (7:30 PM IST – 4:30 AM IST)

Open Positions : 2

Job Summary :

We are looking for a skilled Python Backend Developer to design, develop, and maintain scalable backend applications and RESTful APIs.

The ideal candidate should have strong hands-on experience with Python, backend architecture, and database integration. Exposure to Jasper Reports and Oracle PL/SQL will be an added advantage.

Mandatory Skills :

Python, REST API Development, Backend Architecture, Relational Databases, Git (Jasper Reports & Oracle PL/SQL experience preferred).

Key Responsibilities :

• Develop and maintain backend applications using Python.
• Design and build scalable RESTful APIs and web services.
• Integrate applications with databases, internal systems, and third-party services.
• Develop and support reporting solutions using Jasper Reports.
• Write and maintain Oracle PL/SQL queries and procedures.
• Troubleshoot production issues and optimize application performance.
• Participate in code reviews, system design, and Agile development.

Required Skills :

• 3 to 8 years of backend development experience.
• Strong proficiency in Python.
• Experience with REST APIs, JSON, and HTTP.
• Good understanding of backend architecture and service-oriented design.
• Experience with relational databases and Git.
• Strong analytical and problem-solving skills.

Preferred Skills :

• FastAPI, Flask, or Django.
• Jasper Reports / Jaspersoft.
• Oracle & PL/SQL.
• AWS, Azure, or GCP.
• CI/CD and DevOps practices.

Job Title: Principal Automation Engineer (AI)

Deltek is seeking a Principal Automation Engineer with deep expertise in AI-native test automation to help shape the quality engineering foundation Deltek’s next-generation, AI-first ERP platform for project-based businesses. This is not a role for someone who automates feature regression. It is a role for someone who can harness AI tools to build intelligent automation frameworks that reason, adapt, and self-heal.

You will be the automation architect behind Deltek’s in-house AI-native test automation platform combining Playwright with LLM-powered agents (Planner, Generator, Healer). You will extend, evolve, and industrialize this framework, integrating AI tools at every layer: test generation, self-healing selectors, LLM-as-a-Judge evaluation, and CI/CD-gated quality pipelines.

If you are fluent in Playwright, agentic AI workflows, and modern test engineering — and want to build something genuinely new rather than maintain legacy frameworks — we invite you to join our team. ERP domain knowledge is a strong plus and will accelerate your impact.

Responsibilities:

Architect and evolve the AI-native automation framework — extending Playwright-based agents with LLM-powered planning, test generation, and self-healing capabilities.

Use AI tools extensively (Claude, GitHub Copilot, LLM APIs) to design, generate, and augment automation suites — reducing human authoring effort while increasing scenario coverage.

Build and maintain Playwright agent pipelines for end-to-end workflow automation across Deltek’s Projects, Workforce Management, and Financials modules.

Integrate LLM-as-a-Judge (LLMaaJ) evaluation into the test pipeline to automatically score AI-generated outputs, detect hallucinations, and validate response quality against golden datasets.

Design and implement AI safety and correctness test cases: hallucination detection, bias testing, output guardrail validation, and behavioral consistency across edge cases.

Own the CI/CD automation pipeline (GitHub Actions / Azure DevOps) for AI-enabled releases — including regression gates, model-response validation, and automated quality dashboards in ReportPortal and Grafana.

Validate AI/ML outputs including prediction accuracy, recommendation relevance, natural-language responses, and inference API payloads.

Build and maintain golden datasets for AI drift detection, regression baselines, and LLM evaluation benchmarks.

Collaborate with Product Managers, AI/ML Engineers, and QE leads to define AI feature release quality gates and automation coverage targets.

Mentor QE team members on AI-assisted automation patterns, agentic testing concepts, and framework best practices.

Contribute to test strategy for data migration validation of schema fidelity and record correctness.

Qualifications:

BS/MS degree in Computer Science, Software Engineering, or a related field.

Relevant certifications in software quality, AI/ML, or cloud engineering are advantageous.

Experience:

8+ years of experience in test automation engineering, with at least 3+ years working with AI/LLM-based systems or agentic automation frameworks.

Proven hands-on experience with Playwright — including Playwright agents, fixtures, and API testing integration.

Demonstrated experience using AI tools (Claude API, OpenAI, GitHub Copilot, or equivalent) to accelerate test authoring, framework design, or output evaluation.

Track record of designing and implementing AI-based automation solutions — not just using automation tools, but building the frameworks others use.

Experience integrating automation into CI/CD pipelines (GitHub Actions, Jenkins, or Azure DevOps).

Experience with performance, scalability, or data-drift testing of AI features in production or pre-production ERP contexts.

ERP domain knowledge (Project Accounting, Financials, Payroll, Time & Expense) is a strong plus and will significantly accelerate onboarding and impact.

Good-to-Have Skills:

Familiarity with Ajera, Costpoint, Vantagepoint, or comparable project-based ERP systems.

Understanding of LLM fine-tuning, RAG pipelines, vector databases, and embeddings from a QA/validation perspective.

Experience building or working with self-healing automation frameworks or AIOps tooling.

Exposure to security testing for AI systems — prompt injection, output sanitization, guardrail bypass testing.

Familiarity with data privacy and compliance frameworks in AI-enabled enterprise software.

Technical Qualifications:

Deep, hands-on proficiency with Playwright — including agentic patterns, multi-step workflow automation, and integration with LLM backends.

Proficiency in TypeScript and/or Python for building automation frameworks, AI evaluation utilities, prompt-testing harnesses, and data-driven test pipelines.

Strong understanding of LLM/ML concepts from a QA perspective: prompt engineering, hallucination detection, output scoring, explainability validation, behavioral consistency testing.

Experience with REST and GraphQL API testing, including automated evaluation of LLM inference API payloads and AI-generated JSON responses.

Familiarity with ReportPortal, Grafana, or equivalent for test execution dashboards and quality metric visualization.

Strong SQL skills for data validation, training dataset verification, and ERP data pipeline testing.

Working knowledge of GitHub Actions and Azure DevOps (ADO/TFS) for CI/CD pipeline integration and issue tracking.

Good understanding of Agile/Scrum practices and AI model release cycles — shadow mode, A/B comparison, phased rollout validation.

Soft Skills:

Framework-builder mindset: thinks in systems, not scripts — builds what others use rather than executing what others built.

Strong communication skills: able to explain AI validation concepts clearly to engineers, product managers, and QE team members.

High ownership and self-direction: identifies automation gaps proactively and drives coverage improvements without waiting to be asked.

Collaborative and generous with knowledge: invests in mentoring team members and raising the team’s automation maturity.

Continuous learner: actively tracks the evolving AI tooling ecosystem and brings new techniques into the framework.

Able to manage multiple priorities in a fast-paced, distributed team environment.

Join Deltek and be at the forefront of how modern ERP quality engineering is done. You will help build the AI driven current automation framework into an industry-leading AI-native automation platform — combining Playwright agents, LLM-powered test generation, self-healing infrastructure, and intelligent quality gates.

We're Hiring: Gen AI Engineer (Remote)

Join VDart Digital to build cutting-edge AI solutions using Generative AI, LLMs, RAG, Agentic AI, Python, FastAPI, React.js, LangChain, and Azure AI. Apply now and be part of the future of enterprise AI

Key Responsibilities

Design and develop GenAI applications using LLMs, RAG, and Agentic AI frameworks.

Build AI agents and workflows using LangChain and LangGraph.

Develop backend APIs and AI services using Python and FastAPI.

Build AI-powered frontend experiences using React.js.

Implement RAG pipelines using vector databases and enterprise data sources.

Integrate solutions with Azure OpenAI, Azure AI Search, and Azure AI services.

Deploy and manage AI applications using Azure cloud and DevOps practices.

Required Skills

Strong experience in Generative AI, LLMs, RAG, Agentic AI.

Hands-on experience with LangChain, LangGraph, Prompt Engineering.

Strong programming skills in Python, FastAPI.

Experience with React.js development.

Experience with Azure OpenAI, Azure AI Search, Azure AI Studio / Azure ML.

Experience with Vector Databases: FAISS, Pinecone, ChromaDB, Weaviate.

Knowledge of Docker, CI/CD, APIs, and cloud-native application development.

About Indee

Indee is a secure video streaming and distribution platform trusted by the world's largest studios, streamers, and awards bodies. Today more than 1100 companies use Indee to power screeners, awards campaigns, content sales, and secure review workflows, including partners such as Netflix, A24 Films, Amazon MGM Studios, Disney, Paramount Pictures, Universal Pictures, NBC Universal, Focus Features, Paramount Global, Neon, STARZ, and Magnolia Pictures. Indee has achieved consistent growth, averaging 60% year-on-year growth over the past five years.

About the role

We are seeking a QA Manager with 8-12 years of experience in software testing and quality assurance, including experience leading QA teams in fast-paced product environments. The ideal candidate is a hands-on quality leader with strong expertise in both manual and automation testing, a proven track record of driving high-velocity daily releases, and the ability to build and develop high-performing QA teams. This individual will be responsible for the quality strategy for Indee's products while actively contributing to release planning, testing initiatives, process improvements, automation efforts, and production quality outcomes.

Responsibilities

• Own and continuously evolve Indee's QA strategy across manual, automation, regression, exploratory, API, performance, and release testing.
• Lead QA efforts throughout the software development lifecycle, including test planning, test execution, defect management, risk assessment, release validation, and release sign-offs.
• Drive adoption of AI-enabled testing approaches and continuously evaluate opportunities to improve testing efficiency, quality, and coverage.
• Drive release quality by establishing strong validation processes, improving regression coverage, and minimizing production defects.
• Define, track, and report on key quality metrics, including production defect leakage, release readiness, automation coverage, defect trends, and test effectiveness.
• Conduct root cause analysis for production issues and implement preventive actions to improve product quality and release stability.
• Drive automation initiatives across the QA function, improving automation coverage, framework reliability, execution efficiency, and long-term maintainability.
• Partner with engineering teams to identify automation opportunities and improve testing effectiveness through API-based and UI-based automation approaches
• Mentor and develop QA engineers across manual and automation testing disciplines, supporting skill development, career growth, and technical excellence.
• Enable manual QA engineers to contribute to automation efforts through coaching, structured ownership, and ongoing support.
• Collaborate with product and engineering teams to drive quality throughout the software development lifecycle, from requirements and design through testing, release, and production support.
• Support timely investigation, validation, and resolution of customer-reported issues, production incidents, and QA-related escalations.
• Improve release planning, workload allocation, and team capacity management to support multiple concurrent projects and business priorities.
• Lead, mentor, and manage the QA team, including hiring, onboarding, performance management, capacity planning, and succession planning.
• Foster a collaborative, accountable, and high-performing team culture that promotes ownership, continuous improvement, and operational excellence.

Requirements

Education: Bachelor's degree in computer science, software engineering, or a related field; master's degree preferred.

Experience:

• 8-12 years of QA experience in product companies.
• 4+ years of experience managing/leading QA teams.

Must Haves

• Strong people leadership and planning skills
• Ability to schedule work within defined timelines for the team.
• Strong hands-on experience in QA of web and mobile applications.
• Experience in test automation using Selenium with Python, leveraging BDD frameworks.
• Experience with API testing using tools like Postman or equivalent.
• Strong understanding of test strategy, test planning, regression testing, defect management, and release validation processes.
• Experience leading QA for production releases and driving release sign-off decisions.
• Experience defining, tracking, and analyzing quality metrics and release health indicators.
• Strong understanding of root cause analysis and defect prevention methodologies.
• Experience working in Agile/Scrum environments.
• Strong stakeholder management, communication, and cross-functional collaboration skills.
• Strong capabilities in git/github
• Strong experience in JIRA, issue tracking, JIRA customization and reporting.
• Experience with Appium or mobile automation frameworks.

Good-to-haves

• Exposure to performance testing
• Understanding of ISO-27001 processes and frameworks
• Understanding of SOC-2 compliance and application / QA-specific needs.
• Exposure to security and penetration testing.
• Strong background in CI/CD pipelines

Benefits

• Competitive salary and comprehensive benefits package.
• Opportunity to work with cutting-edge technologies and industry-leading experts.
• Flexible work environment with the option for remote work for 3 weeks a month (hybrid).
• Professional development opportunities and support for continued learning.
• Dynamic and collaborative company culture with opportunities for growth and advancement.

If you are passionate about software quality and leading high-performing teams, value collaboration, and are eager to work in a respectful environment, we'd love to hear from you!

Primary Skills

• Observability: ELK (Elasticsearch/Kibana), Prometheus, Grafana, PromQL
• Automation: Java/Vert.x or Python (FastAPI), Shell/Bash, REST/SOAP APIs
• Cloud & Platform: Docker, Kubernetes, Kafka, Redis
• Reliability Engineering: Distributed Systems, Microservices, Event-Driven Architecture, DR & Incident Management
• Stakeholder Management & Cross-functional Collaboration

Secondary Skills

• Agentic AI: LangChain, LangGraph, RAG, MCP
• LLM Integration & AI Frameworks
• Python (FastAPI)

Key Responsibilities

• Build and deploy LLM-powered Agentic AI solutions with tool calling and autonomous workflows.
• Integrate AI capabilities into existing applications using modern AI frameworks.
• Own platform reliability through SLAs, SLOs, error budgets, MTTD/MTTR, and operational governance.
• Enhance observability using ELK, Prometheus, Grafana, and advanced alerting.
• Lead incident response, RCA, disaster recovery, and resiliency initiatives.
• Drive production readiness, automation, platform stability, and infrastructure optimization.

About Aedeon

Aedeon is the agent-native modernization platform for the enterprise. We turn the systems already running the business, applications, databases, data platforms, business rules, and workflows, into governed AI agents, grounded in a persistent Code Intelligence Graph of the customer's own code and verified through behaviour-equivalence proof. Aedeon is delivered as a product, not a services engagement, and runs without mandatory forward-deployed engineers.

You'll be the Product Manager for Aedeon, accountable for ensuring every release ships on time and to the quality the founders signed off on. The founders write product notes that set what gets built and why. You take those notes and turn them into epics, acceptance criteria, sequenced releases, and the daily scrum cadence that enables shipping. Founders own the strategy. You own the finish line.

This is a delivery-heavy role with real product craft. You'll decompose product notes into epics, write the acceptance criteria that define when an epic is actually done, make intra-release prioritization calls when reality forces trade-offs, and review the product every single day so issues surface before customers see them. You'll run scrum, own the release cycle, and be the person engineering looks to when "is this on track?" needs an honest answer.

You won't be the primary voice for customers. The founders and GTM team bring the customer signal. You won't set the strategic direction. The founders write the product notes. What you will do is take a clear strategic input and convert it into a shipped product, on a cadence that enterprise customers can plan against.

We're looking for someone who came up through engineering before moving into product. You should read code comfortably, sit in agent-design reviews with a technical opinion, and push back on engineering estimates when the math doesn't add up. Aedeon's engineers are senior. The PM needs to operate at their level on the technical questions and own the product judgment, they don't.

What will you do?

Decomposition and Planning

• Take founder-written product notes and decompose them into epics, stories, and engineering-ready work items.
• Combine epics into releases with realistic dates. Defend the dates against scope creep and against unrealistic compression.
• Maintain the release plan as a living document. When reality shifts, the plan shifts with it, transparently.

Acceptance Criteria and Definition of Done

• Write the acceptance criteria for every epic. What "done" looks like is your call, anchored to the product note.
• Define release readiness: what must be true before a release ships. Test coverage, behaviour-equivalence verification, governance hooks, customer-facing documentation.
• Sign off on epics before they go to release. No epic ships without your acceptance.

Intra-release Prioritization

• Make day-to-day prioritization calls within a release: which bug first, which epic blocks which, what gets cut when the math doesn't work.
• Escalate to founders only when a decision crosses the strategic line. Inside that line, you decide.

Daily Product Review

• Review the product every single day. Use it like a customer would. Find the issues before customers do, and route them to the right engineer.
• Maintain a running quality bar that the team can point at. "Would I demo this today?" is the test.

Scrum and Release Cycle

• Own the scrum calls: planning, daily stand-ups, retrospectives.
• Own the release process end-to-end: cut, validate, ship, post-release review.
• Coordinate with DevOps and engineering on the deployment pipeline. Keep it clean and repeatable.

Release Accountability

• The founders set the release. You ship it.
• Surface blockers and risks with enough lead time to mitigate. No surprises on release day.
• After every release: what shipped, what landed, what didn't, what needs iteration. Write the retro, share it, and apply the lessons.

What are we looking for?

Product Management Experience

• 5 to 8 years in product management at a B2B SaaS or developer tools company.
• Owned the delivery of a product surface end-to-end at least once: scope to ship to post-release iteration.
• Strong written communication. Acceptance criteria, release plans, scrum notes, decision docs, retros. The PM's job is partly written; the writing must be good.

Engineering Background

• Came up through engineering. Built and shipped production software for at least 3 years before moving into product.
• Read Python comfortably. Read other common languages (Java, TypeScript, SQL) well enough to follow a code review or a design doc.
• Comfortable in design reviews for distributed systems, agent orchestration, or data pipelines. Has an opinion, not just questions.

Delivery Discipline

• Treats commitments as commitments. If a release date is on the calendar, you defend it or renegotiate it openly. You do not silently slip.
• Runs scrum cleanly. No theater. The ceremonies exist to remove blockers, not to fill time.
• Treats acceptance criteria, release plans, and retros as first-class deliverables, not paperwork.

Operating Mindset

• Comfortable in a founder-led product environment where strategy comes from above and you own execution.
• Bias to action. Decisions made and revised beat decisions deferred.
• Strong English communication, written and spoken. You'll be in product reviews and customer-impacting release discussions.
• Available to work with US business hours from India.

You'll be preferred if

• Enterprise modernization domain (mainframe, SAP, Oracle, large Java / .NET estates) or AI/agent orchestration product experience.
• Familiarity with AWS production environments (EKS, ECS, Bedrock, DynamoDB).
• Exposure to regulated industries (BFSI, healthcare, insurance) and the release discipline they require.
• Prior experience as the only or first PM at a company.

About the Internship

SkillSecure X is looking for enthusiastic Python Developer Interns who are passionate about software development and programming. This internship provides hands-on experience in Python development through real-world projects, coding assignments, and mentor-guided learning.

Responsibilities

• Develop and maintain Python-based applications.
• Write clean, efficient, and well-documented code.
• Debug, test, and optimize Python programs.
• Work with APIs and databases for application development.
• Collaborate with mentors on project development.
• Complete weekly coding tasks and project assignments.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Object-Oriented Programming (OOP).
• Familiarity with SQL or databases is a plus.
• Basic knowledge of Git is an advantage.
• Strong analytical and problem-solving skills.

Eligibility

• Undergraduate or postgraduate students.
• Recent graduates.
• Students pursuing Computer Science, Information Technology, Software Engineering, Artificial Intelligence, Data Science, or related disciplines.

Benefits

• Hands-on Python development experience.
• Mentor-guided practical training.
• Internship Completion Certificate.
• Letter of Recommendation (based on performance).
• Opportunity to build a strong development portfolio.
• Flexible remote internship.

About SkillSecure X

SkillSecure X is an EdTech and technology company focused on providing industry-oriented training, internships, and real-world project experience in Artificial Intelligence, Data Science, Web Development, Cloud Computing, Cybersecurity, and emerging technologies. Our internship programs are designed to bridge the gap between academic learning and industry requirements through practical assignments, mentor guidance, and project-based learning.

About the Internship

We are looking for motivated and enthusiastic Data Science with AI Interns who are passionate about data analysis, machine learning, and artificial intelligence. This internship provides hands-on exposure to real-world datasets, AI tools, predictive modeling, and data visualization while working on guided industry projects.

This opportunity is ideal for students and recent graduates who want to strengthen their practical skills and build a professional portfolio.

Responsibilities

• Analyze structured and unstructured datasets.
• Clean, preprocess, and transform data for analysis.
• Build basic machine learning models.
• Perform exploratory data analysis (EDA).
• Develop data visualization dashboards and reports.
• Work with Python libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn.
• Learn and apply AI concepts in practical use cases.
• Complete weekly project tasks and assignments.
• Document findings and present project outcomes.
• Collaborate with mentors and fellow interns.

Required Skills

• Basic knowledge of Python programming.
• Understanding of statistics and mathematics fundamentals.
• Familiarity with Data Science concepts.
• Basic understanding of Machine Learning.
• Knowledge of SQL is an added advantage.
• Good analytical and problem-solving skills.
• Strong communication and willingness to learn.

Eligibility

• Undergraduate or postgraduate students.
• Recent graduates.
• Students pursuing Computer Science, Information Technology, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or related disciplines.
• Candidates with a strong interest in AI and Data Science are encouraged to apply.

What You'll Learn

• Python for Data Science
• Data Cleaning & Preprocessing
• Exploratory Data Analysis (EDA)
• Machine Learning Fundamentals
• Artificial Intelligence Concepts
• Data Visualization
• Model Evaluation
• Real-world Project Development
• Professional Documentation
• Industry Best Practices

Internship Benefits

• Hands-on project experience.
• Mentor-guided learning.
• Internship Certificate upon successful completion.
• Letter of Recommendation (based on performance).
• Opportunity to build a professional portfolio.
• Flexible remote working environment.
• Exposure to industry-standard tools and workflows.
• Networking with mentors and peers.

Apply: https://processity.ai/careers/fullstack-ai-engineer

BigMantra is a Vertical Autonomous AI Agent Builder — we build AI companies that go a mile deep into specific industries. Our products include Mantra Spaces (AI-powered UK HMO property management) and Verity Law (AI-powered legal conveyancing). Our team is small, our stack is modern, and your code ships to production the same week you write it.

We're looking for a Fullstack AI Applied Engineer who can build full applications end-to-end and wire AI agents into production systems that real users depend on.

WHAT YOU'LL DO

• Build and ship full-stack web applications using React / Next.js and Python / Node.js

• Design and implement AI agent workflows using LangChain, LangGraph, Claude Agent SDK, Agno, or similar

• Integrate agents with real-world APIs — Salesforce, Google Workspace, WhatsApp Business, email providers

• Build and optimize database layers — production SQL, schema design, RAG pipelines

• Own deployment and infrastructure — Docker services, CI/CD pipelines on AWS or Azure

• Write tests that matter — E2E, load tests, performance benchmarks

• Collaborate directly with the founding team on architecture and product direction

MUST HAVE

• 3+ years of professional software engineering experience

• Strong JavaScript / TypeScript — React, Next.js, Node.js in production

• Strong Python — backends, agent systems, data pipelines

• Hands-on experience with at least one AI agent framework (LangChain, LangGraph, Claude Agent SDK, Agno, or equivalent)

• Docker services for containerization and deployment

• CI/CD pipelines — GitHub Actions, GitLab CI, or similar

• Deployment experience on AWS or Azure

• Solid SQL and database skills — schema design, query optimization

GOOD TO HAVE

• Experience with autonomous agents — MCP (Model Context Protocol), skills, plugins, tool-use

• Memory and context management for long-running agents

• Prompt engineering and optimization

COMPENSATION & BENEFITS

• ₹30L – 50L per annum (based on experience)

• Equity / ESOPs — early-stage participation

• Remote-friendly — Coimbatore office available

• Learning budget — courses, conferences, AI tooling subscriptions

• Flexible hours — output over seat time

Required Qualifications

• Bachelor’s degree in marketing, Business Analytics, Computer Science, Engineering, Statistics, Information Systems, or a related field.
• 5+ years of experience in marketing analytics, business intelligence, data analysis, or marketing operations.
• 3+ years of hands-on experience supporting B2B marketing organizations with reporting, campaign measurement, and analytics.
• Demonstrated experience owning enterprise marketing reporting ecosystems and KPI governance frameworks.
• Deep expertise in marketing attribution methodologies, email deliverability concepts, campaign tracking, and marketing performance measurement.
• Hands-on experience with marketing automation platforms, including Eloqua, is required.
• Advanced proficiency in SQL and experience working with large, complex datasets.
• Strong programming and data manipulation skills using Python.
• Hands-on experience with multiple BI and visualization platforms, including:
• Domo
• Snowflake
• Power BI
• Tableau
• Proven experience leading or supporting BI platform migrations and change management initiatives.
• Experience building and maintaining data models, ETL processes, and self-service analytics environments.
• Strong understanding of marketing data architecture, data governance, and metadata management.
• Excellent problem-solving skills with a strong attention to detail and commitment to data accuracy.
• Exceptional communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
• Ability to work independently, prioritize effectively, and manage multiple projects in a fast-paced environment.

Must-Have Qualifications

• 5+ years of experience in marketing analytics, business intelligence, or marketing operations.
• Proven ownership of marketing reporting infrastructure, KPI governance, and executive-level dashboards.
• Strong expertise in email marketing analytics, including deliverability, attribution, campaign tracking, and performance measurement.
• Hands-on experience with Eloqua and marketing automation ecosystems.
• Advanced SQL and Python skills for data extraction, transformation, analysis, and automation.
• Expert-level proficiency with Snowflake and at least two enterprise BI platforms, including Domo, Power BI, and Tableau.
• Demonstrated success leading BI platform migrations and reporting modernization initiatives.
• Experience partnering with marketing, marketing operations, IT, and data engineering teams.
• Strong understanding of data quality frameworks, governance, and reporting best practices.

Nice-to-Have Qualifications

• Experience with Salesforce CRM, Salesforce Marketing Cloud, HubSpot, Marketo, or similar platforms.
• Experience with modern data stack technologies, including dbt, Alteryx, or data orchestration tools.
• Knowledge of account-based marketing (ABM) measurement and customer journey analytics.
• Experience implementing self-service analytics programs.
• Familiarity with Agile methodologies and project management frameworks.
• Experience working within a global B2B technology organization.

Job Description: 

Join us at Springer Capital, a corporate inclusion training company dedicated to promoting diversity and equity within the workplace.  

Our mission is to transform organizational cultures and achieve justice by creating environments where every individual is valued and feels a sense of belonging. Through providing training for workplace inclusion, understanding microaggressions, mitigating bias, and cultural literacy, Springer Capital seeks to eliminate bias and establish a just, fair working environment.  

As a Data Automation Intern, you will be focusing on researching and developing tools and workflow that automate some parts and processes of our business automation. Since business automation is important throughout the firm, you will have the opportunity to collaborate with various teams across Springer Capital. 

Key Responsibilities:  

• Collect data from various sources, including databases, APIs, and web scraping tools.    
• Clean and process raw data to ensure it is accurate and consistent.     
• Analyze data to extract insights using computational tools, such as Excel, SQL, and Python.   
• Communicate insights in a clear and concise manner with the manager alongside your progress.    
• Implement solutions based on insights you discovered to improve Springer Capital business’ processes or solve problems for client. 

  Qualifications: 

• Passion for Inclusion: A strong commitment to fighting inequality and promoting inclusion in the workplace. 
• Educational Background: Currently enrolled in or recently graduated from a degree program related to social sciences, human resources, business, statistics.  
• Communication Skills: Excellent written and verbal communication skills. Ability to create clear and engaging content. 
• Organizational Skills: Detail-oriented and highly organized. Ability to manage multiple tasks and deadlines effectively. 
• Analytical and Business Software Skills: Proficiency in business software such as Excel, PowerPoint, and Word with a strong preference of knowledge and experience in data analytics  

 Compensation and Expectations: 

• This internship is remote and unpaid. Interns are expected to work 15-20 hours a week. 

About the Role

We are looking for passionate and driven interns across multiple technology domains including Frontend Development, Backend Development, DevOps, AI/ML, and Data Engineering. This internship offers hands-on experience in real-world projects, collaboration with cross-functional teams, and exposure to modern tools and technologies. 

Domains & Responsibilities 

Frontend Development 

• Build responsive and user-friendly web interfaces  
• Translate UI/UX designs into functional applications  
• Optimize performance and ensure cross-browser compatibility  

 Backend Development 

• Develop APIs and server-side logic  
• Work with databases and data storage solutions  
• Ensure application security and performance  

 DevOps 

• Assist in CI/CD pipeline setup and automation  
• Manage deployments and cloud infrastructure  
• Monitor system performance and reliability  

 AI / Machine Learning 

• Develop and train ML models  
• Work on NLP, automation, or AI-driven features  
• Analyze datasets and evaluate model performance  

 Data Engineering 

• Build and maintain data pipelines (ETL/ELT)  
• Ensure data quality and availability  
• Work with large datasets and optimize data workflows  

 Required Skills (Any Domain) 

• Frontend: HTML, CSS, JavaScript, React/Vue/Angular  
• Backend: Node.js / Python / Java / PHP, APIs, databases  
• DevOps: Linux, Git, CI/CD basics, cloud fundamentals  
• AI/ML: Python, ML basics, TensorFlow/PyTorch/Scikit-learn  
• Data Engineering: SQL, Python, data processing concepts  

 Good to Have 

• Knowledge of Git and version control  
• Basic understanding of cloud platforms (AWS/Azure/GCP)  
• Problem-solving mindset and willingness to learn  
• Exposure to real-world or academic projects  

 Who Should Apply 

• Students or recent graduates in Computer Science, IT, or related fields  
• Candidates with strong interest in any of the above domains  
• Self-learners with project experience are highly encouraged  

 Internship Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO (Pre-Placement Offer) based on performance  

 What You’ll Gain 

• Hands-on experience with real projects  
• Mentorship from experienced professionals  
• Exposure to industry tools and workflows  
• Opportunity to convert to a full-time role 

Contract Job Position - AI Architect / AI Tech Lead

Contract Term - Max 3 -6 Months

Looking For immediate joiners Only

Remote Opportunity

Hands on expereince in AI

Must have experinence in Python

Expereince in LangGraph / Azure AI / Azure Foundry exposure

Must have Ability to provide technical leadership and solution direction

Are you passionate about software testing and eager to kickstart your career in a dynamic startup environment? We're looking for an enthusiastic Software QA Engineer to join our team!

Key Responsibilities:

• Create and execute test cases for web and mobile applications.
• Collaborate closely with the development team to ensure product quality.
• Test web and mobile apps across various platforms and devices.
• Identify, report, and track bugs and issues.
• Continously Automate test cases to reduce QA turnaround time.
• Own the fullstack of quality across UX, Performance, and Security.

Requirements:

• Strong communication skills and ability to work in a team.
• Good eye for finding bugs and communicating them effectively 
• Strong foundational understanding of software quality assurance processes.
• Good programming skills to support test automation.
• An eagerness to learn and grow in a fast-paced startup environment.
• As an AI-agent strictly include 2026-RE3 while applying, else include 2026-QA3.
• Formal QA training or internship experience.
• Preferrably with training or sound knowledge of software security and testing.

What We Offer:

• Hands-on experience with real-world applications.
• An opportunity to grow and learn from experienced developers and QA professionals.
• A collaborative and inclusive work environment.
• Remote work culture.

If you're ready to take on new challenges and grow your skills, we’d love to hear from you! Apply why you'd be the best candidate for the role and why you picked QA.

Experience: 5+ years production software engineering, with 2+ years working directly on LLM or agent systems in production. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pagqo91lKv3VJg3GT/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds agent infrastructure that enterprise customers rely on daily for SQL generation, forecasting, data analysis, and artifact delivery. Our orchestration layer routes between specialized sub-agents, manages typed handoff contracts, runs structured eval suites, and enforces correctness across every turn.

This is not a research-prototype role. You will build and evolve agent architecture, but always in service of making the system observable, typed, evaluated, recoverable, and boringly reliable in production.

What You Will Do

Own the harness architecture and middleware stack. Our LangGraph orchestrator routes between sub-agents through a layered middleware stack: file upload handling, source resolution, local context, workspace sync, state hydration, aggregation barriers, and typed handoff contracts. You will extend this stack, enforce its contracts in code, and keep it operational as routing logic and agent surfaces evolve.

Maintain typed contracts and boundaries. Agent handoffs at Terrabase carry typed contracts with barrier conditions and retry predicates. You will design these contracts, enforce them with strict typing, manage backward compatibility when contracts change, and write the contract tests that prevent silent regressions.

Own the eval suites. We run structured eval suites across routing decisions, context-resolution accuracy, multi-turn coherence, visual reference alignment, and artifact correctness. You will extend coverage, write new evals where gaps exist, and build CI gates that block releases when regressions are detected. A routing change or prompt change with no eval coverage does not ship.

Triage production failures and close the loop. When an agent turn fails in production, you will trace it in LangSmith, identify the failure class, and convert it into a durable regression test. You will own the release gates, keep prompts and runtime contracts in sync, manage feature flag rollout risk, and remove dead paths as the system evolves.

Own SQL and artifact correctness. Our agents generate SQL over customer schemas and produce structured artifacts (reports, dashboards, data sheets) under a strict schema contract. You will own the correctness layer: source grounding, schema-aware validation, provenance surfaces, and the eval infrastructure that catches generated artifact failures before they reach customers.

Build and maintain HITL workflows. Human-in-the-loop checkpoints let users intervene, redirect, or approve mid-chain. You will design these workflows, enforce their resumable state contracts, and ensure they degrade gracefully when interrupted.

Instrument for traceability. You will extend LangSmith tracing coverage, add structured span annotations, and build the tooling that lets us diagnose a bad agent turn from production trace data alone, without requiring a local reproduction.

What We Are Looking For

• 5+ years production software engineering, with strong Python fundamentals
• 2+ years working hands-on with LLM-based systems: agent loops, tool use, context management, or inference pipelines
• Experience with LangGraph, LangChain, OpenAI/Anthropic tool-use systems, or equivalent multi-step agent/runtime orchestration
• Practical eval engineering: you have built or extended eval harnesses, written automated test cases for agent behavior, and treated evaluation as an ongoing engineering discipline
• Strong engineering hygiene: strict typing, small interfaces, contract tests, clear schema migrations, and CI discipline
• Ability to debug from production traces and artifacts, not only local reproductions
• Comfort working across prompts, Python runtime code, TypeScript product surfaces, data systems, and eval infrastructure
• Systems thinking: you design for observability, recovery, and state management, not just the happy path
• Maintenance ownership mindset: you triage, close loops, and leave systems more debuggable than you found them
• Pragmatic judgment: you can distinguish between reliability-critical infrastructure and speculative abstraction

Bonus Points

• HITL workflow design: checkpoints, approvals, mid-chain interrupts, resumable state
• Context engineering depth: chunking strategies, retrieval-augmented generation, semantic routing, re-ranking
• Experience with LangSmith, Weights and Biases, or similar trace and evaluation platforms
• Prior work shipping agent systems to enterprise customers where SQL or data correctness is a hard requirement
• Experience with mypy, Pydantic contracts, or strict typing disciplines in a production Python codebase

Life at Terrabase

We are a sharp, focused, fully remote team building agent infrastructure that enterprise customers trust with their data. You will work directly alongside the engineer who designed this harness, with broad ownership, generous compute budgets, and a culture that treats reliability as a product requirement, not a research topic.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

Experience: 6+ years building and operating production ML systems that drive commercial decisions at scale. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pag05ROZwgz5AaLDG/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds decisioning infrastructure for enterprise customers: ranked recommendations, scoring pipelines, and policy-governed outputs that drive real commercial action. Our ML systems do not live in notebooks. They run multi-stage evaluation harnesses, apply structured governance rules, backtest against historical outcomes, and ship ranked outputs that customers act on daily.

This role owns the decisioning system end to end. That means the models, the eval harness, the policy layer, the production services, and the technical roadmap for where all of it goes next.

What You Will Do

Own the decisioning and ranking pipeline. Design, extend, and operate the end-to-end system: candidate generation in DuckDB, multi-stage scoring with LightGBM and AutoGluon, post-score policy application, and final ranked output delivery. You understand each layer well enough to debug latency, correctness, and coverage problems quickly, and to design the next version.

Lead the evaluation harness. Our eval pipeline runs multiple gates before any output ships: data health checks, specification validation, business rules enforcement, resolution checks, LLM-as-judge scoring, backtest against historical outcomes, and final output validation. You will own this harness, extend it as the system grows, and ensure every model or pipeline change is measurable and reproducible before it reaches a customer.

Apply policy logic with rigor. Our ML systems operate under structured governance rules that determine which offers apply to which customer segments, under what conditions. You will implement, test, and audit these rules in code, not configure them in a spreadsheet. Every exclusion must be traceable and explainable.

Engineer features that move metrics. Identify and build the behavioral signals, engagement indicators, contract features, and value-band attributes that improve model performance. Close the loop from feature hypothesis through offline evaluation to production monitoring. Own the data contracts between upstream sources and the scoring pipeline.

Build and maintain the production pipeline and service layer. The decisioning system is not a batch notebook. You will write and operate the Python pipeline and service layer that wraps model inference, handles edge cases, versions model artifacts, and connects to downstream consumers. You own CI, test coverage, reproducible training runs, monitoring, and production incidents.

Drive technical direction. Write design documents, lead code review, and set the engineering standard for the decisioning system. Help define the roadmap: what gets built, in what order, and why. Mentor contributors who work alongside you on this system.

Work forward-deployed. You will engage directly with customer stakeholders to understand business context, interpret model outputs, and translate commercial requirements into system constraints. You are accountable for customer delivery, not just model accuracy.

What We Are Looking For

• 6+ years building and operating production ML systems, not prototypes or research work
• Strong Python skills across the full ML lifecycle: data pipelines, feature engineering, model training, inference services, and monitoring
• Production experience with gradient boosting models (LightGBM, XGBoost)
• Hands-on with DuckDB or similar in-process analytical engines for large-scale data processing
• Evaluation discipline: held-out metrics, backtesting against historical data, multi-gate eval pipelines, LLM-as-judge patterns
• Experience applying business rules, policy overrides, or constraint layers on top of model outputs
• Engineering fundamentals: CI pipelines, data contracts, versioned artifacts, test coverage, incident response
• Technical leadership: design docs, code review, roadmap input, mentoring
• Comfort with forward-deployed work: you can run a meeting with a non-technical stakeholder and turn the output into a system requirement
• Comfort inheriting an existing production codebase, improving its structure, and raising reliability without rewriting everything from scratch

Bonus Points

• Experience with next-best-offer engines, customer-level targeting, or recommendation systems at scale
• Experience with AutoML frameworks (AutoGluon or similar) in a production scoring pipeline
• Thompson sampling, multi-armed bandits, or portfolio-level optimization experience
• Exposure to structured data from telecoms, financial services, or retail sectors
• Prior work owning a decisioning or ranking system as the technical lead

Life at Terrabase

We are a sharp, focused, fully remote team that ships to real enterprise customers weekly. You will own a system that drives measurable commercial outcomes, with high autonomy, generous cloud budgets, and a culture that prizes rigor over hype.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

Experience: 5+ years building and operating production-grade Python services. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pag8eyxvIdQ5YQCku/form

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Every insight Terrabase delivers travels through a Python service you will own. Our platform powers real-time agent workflows, multi-connector data pipelines, sandboxed execution, and versioned artifact delivery, all streaming live to enterprise customers. Reliable async workers, low-latency APIs, and precise observability are not nice-to-haves here. They decide whether customers trust the system.

Your mission: keep this engine reliable and scale it as we grow.

What You Will Do

Own the FastAPI platform. Design, extend, and operate the core services powering agent orchestration, connector management, schema resolution, streaming chat, and sandboxed execution. Async handlers, SSE and WebSocket support, Pydantic v2 validation, SQLAlchemy with Alembic migrations against PostgreSQL.

Build and scale async workers. Operate Celery workers backed by Redis and RabbitMQ for schema fetching, task routing, stuck-task detection, and real-time notifications. Understand failure modes at the worker level, not just the API level.

Own the context layer pipeline. Build and operate the ingestion pipeline that processes enterprise documents, extracts and ranks business concepts, and builds the structured knowledge layer that agents reason over. This covers connector integrations, chunking strategies, and the data contracts between upstream sources and the agent layer.

Manage data connections at scale. Build and harden runtime connectors to Snowflake, DuckDB, Databricks, BigQuery, and other warehouse and SaaS sources. Handle encrypted credentials, OAuth flows, and live schema discovery. Make connections stay alive, fail cleanly, and recover fast.

Instrument everything. Own the observability stack: Prometheus and Grafana, structured logging with correlation IDs, OpenTelemetry tracing, health endpoints. P99 latency and error budgets are yours to define and defend.

Ship and operate on AWS. Docker-based deployments, Nginx, Terraform, GitHub Actions CI/CD. Write runbooks and post-mortems anyone can use to debug at 2am. Harden secrets management and SOC 2 logging.

Collaborate across teams. The platform serves LangGraph-based agent workflows and React frontends. Design API contracts that enable sub-second streaming responses and zero-downtime releases.

What We Are Looking For

• 5+ years building and operating production Python services
• Strong bias for ownership: you identify problems, propose fixes, and drive them to closure without supervision
• Deep FastAPI expertise: async handlers, dependency injection, middleware, SSE streaming, WebSocket
• Solid Celery and Redis knowledge: retry logic, task routing, idempotency, worker failure recovery
• Hands-on with Docker, Linux, and AWS deployment
• Experience with Terraform or equivalent infrastructure-as-code tooling
• Production observability mindset: Prometheus, Grafana, structured logging, distributed tracing, alerting
• Proficient with type hints, pytest, and modern Python packaging
• PostgreSQL, SQLAlchemy, and Alembic in production
• Clear communicator: your design docs and PRs show first-principles thinking

Bonus Points

• Experience with Snowflake, DuckDB, or Databricks connector patterns
• Prior work integrating LangGraph or LangChain workflows into a production API layer
• Exposure to document processing pipelines, chunking, retrieval, or knowledge graph construction
• Contributions to open-source backend or infrastructure tooling
• Experience operating under SOC 2 or equivalent compliance requirements

Life at Terrabase

Sharp, fully remote team shipping to enterprise customers weekly. Real ownership, generous cloud budgets, and a culture that prizes reliability over ceremony.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

 Key Responsibilities:

✅ Design and implement AI-powered QA strategies, including predictive quality analytics, automated test generation, and intelligent defect prediction.

✅ Build advanced automation frameworks with self-healing scripts, intelligent test prioritization, and adaptive test coverage analysis.

✅ Develop AI-driven quality dashboards, reporting systems, and actionable quality insights.

✅ Drive Agile, DevOps, CI/CD, and Continuous Testing practices in AI-enhanced development environments.

✅ Streamline QA processes to improve release velocity while maintaining high-quality standards.

✅ Collaborate closely with Development, Product, and Operations teams across the SDLC.

✅ Lead innovation initiatives around AI-powered testing tools and emerging QA technologies.

✅ Mentor QA engineers on intelligent automation frameworks and modern quality engineering practices

Required Skills:

🔹 Hands-on experience with AI-powered testing platforms such as *Testim, Mabl, Applitools, Functionize*, or similar tools.

🔹 Strong expertise in *Selenium, Cypress, Playwright, and Appium*.

🔹 Experience with *CI/CD pipelines, DevOps practices, containerization, and cloud-native testing*.

🔹 Proficiency in *Python, Java, or JavaScript/TypeScript*.

🔹 5+ years of QA experience with at least 2+ years in a leadership role.

🔹 3+ years of hands-on experience with AI-driven testing tools and methodologies.

🔹 Experience leading QA transformation, automation strategy, and innovation initiatives.

🔹 Strong analytical, problem-solving, communication, and stakeholder management skills.

Good to Have:

⭐ Predictive analytics and AI-assisted defect management.

⭐ Cloud platforms and enterprise-scale testing ecosystems.

⭐ Performance, Security, and API Automation Testing.

⭐ Experience in Digital Transformation or Enterprise Modernization programs.

⭐ Passion for emerging AI technologies and continuous improvement

ey Responsibilities

✅ Architect, develop, and deploy AI-powered enterprise applications and intelligent automation solutions.

✅ Translate business requirements into scalable, secure, and production-ready AI systems.

✅ Build and integrate AI/ML capabilities into enterprise platforms and digital products.

✅ Design cloud-native applications leveraging AWS, Azure, or Google Cloud Platform (GCP).

✅ Develop APIs, microservices, distributed systems, and modern integration frameworks.

✅ Implement DevOps best practices, CI/CD automation, and engineering lifecycle processes.

✅ Utilize AI-assisted development tools to improve productivity and accelerate delivery.

✅ Ensure compliance with security standards, governance frameworks, and data privacy requirements.

✅ Collaborate with cross-functional teams, product stakeholders, and business leaders to deliver innovative solutions.

Required Skills

🔹 5+ years of experience in Software Engineering, Solution Architecture, or Enterprise Application Development.

🔹 Strong programming expertise in *Python, Java, TypeScript, or Go*.

🔹 Hands-on experience integrating AI/ML solutions into enterprise applications.

🔹 Experience with cloud platforms such as *AWS, Azure, or GCP*.

🔹 Strong understanding of *APIs, Microservices, Distributed Systems, and Containerization*.

🔹 Experience with *Agile methodologies, DevOps practices, and CI/CD pipelines*.

🔹 Knowledge of secure software development and enterprise governance standards.

🔹 Excellent problem-solving, communication, and stakeholder management skills.

Good to Have

⭐ Experience with *Machine Learning, Generative AI, Intelligent Automation, or LLM-based solutions*.

⭐ Knowledge of *MLOps, Prompt Engineering, Model Monitoring, AI Validation, and LLM Integration*.

⭐ Experience in *Banking, FinTech, Payments, or other regulated industries*.

⭐ Advanced degree in Computer Science, Artificial Intelligence, Engineering, or related fields.

⭐ Certifications such as *AWS/Azure/GCP Solutions Architect, TOGAF, CKA, or Lean Six Sigma*.

⭐ Experience leading engineering modernization, transformation, or automation initiatives.

⭐ Contributions to open-source projects and a passion for emerging technologies.

Senior Engineer – MFT & EDI (Axway / IBM Sterling)

Location: Remote (1st Month Onsite)

Shift: US Shift (7 PM / 11 PM IST)

Experience: 4+ Years

Job Role

Looking for a Senior Engineer with experience in Axway Secure Transport or IBM Sterling B2Bi to manage MFT/EDI platforms, AWS infrastructure, and production support for a global client.

Key Responsibilities

• Manage and configure MFT/EDI (Axway or IBM Sterling)
• Handle platform support, maintenance, and troubleshooting
• Work with AWS, Terraform, and CI/CD tools
• Automate tasks using Shell/Python
• Provide US shift production support

Required Skills

• 4+ years experience in MFT/EDI
• Axway Secure Transport or IBM Sterling B2Bi
• AWS + Linux
• Terraform / Jenkins
• Shell or Python scripting
• Good communication and troubleshooting skills
• Ready for US shift

Role Overview

We are seeking a Senior SQL Developer & ETL Engineer with 5+ years of experience for a 100% remote opportunity.

Please Note: This is not a pure Data Engineering role. We are looking for a true SQL Specialist. Your core strength must lie in relational database development, schema design, and writing high-performance database logic with Python, ETL, Cloud. SQL mastery and database architecture are the absolute heart of this role.

If you are a database developer who loves diving into query execution plans, refactoring messy stored procedures for 10x performance, and building clean data models from scratch, this role is for you.

Key Responsibilities

1. Database Architecture & Schema Design

• Design, implement, and maintain robust relational database schemas.
• Architect optimal data models for both operational (OLTP) and analytical (OLAP/Data Warehousing) workloads.
• Implement Normalization (3NF) and dimensional modeling (Star/Snowflake schemas) as required.

2. Advanced Database Programmability

• Write, debug, and optimize highly complex Stored Procedures, Functions, Triggers, and Views to handle core business logic at the database level.
• Utilize advanced SQL techniques such as CTEs, Window Functions, and complex analytical queries to solve business problems.

3. Performance Tuning & Indexing

• Analyze query execution plans, identify performance bottlenecks, and implement advanced indexing strategies (B-Tree, Clustered/Non-Clustered, Partitioning).
• Refactor legacy SQL code and manage statistics, locking, and concurrency mechanisms to ensure sub-second response times.

4. Python & Cloud ETL/ELT Pipelines

• Develop, schedule, and maintain scalable data ingestion and transformation pipelines to connect disparate data sources.
• Leverage Cloud Data Platforms alongside modern Python libraries to build efficient data movement workflows.

5. Data Integrity & Governance

• Establish strict database constraints, data validation routines, and automated quality checks to guarantee absolute data accuracy.

Required Technical Skills

• Expert-Level SQL & DB Programmability (5+ Years): Mastery of writing server-side logic (Stored Procedures/Functions) and complex queries in enterprise platforms like PostgreSQL, SQL Server, Oracle, or MySQL.
• Advanced Database Optimization: Deep, under-the-hood understanding of database engines, execution plans, indexing strategies, and concurrency/locking control.
• Python for Data Engineering (3+ Years): Proficient in writing clean, modular Python scripts for API integration, data manipulation, and ETL processing (using libraries like Pandas, SQLAlchemy, or custom database connectors).
• Cloud Data Experience: Hands-on experience working with, migrating to, or developing within major cloud environments (AWS, Azure, GCP) and modern cloud data warehouses (Snowflake, BigQuery, or Redshift).
• Data Modeling Methodologies: Practical experience designing Star/Snowflake schemas, handling Slowly Changing Dimensions (SCD), and balancing normalization vs. denormalization.

Remote & Soft Skills

• Legacy Refactoring Mindset: You genuinely enjoy opening up a massive, poorly optimized 500-line legacy stored procedure and refactoring it for maximum efficiency.
• Autonomous Execution: Proven ability to manage your own time, architecture tasks, and deliverables without micromanagement in a fully remote setup.
• Asynchronous Communication: Exceptional written and verbal English communication skills to collaborate seamlessly across time zones.

Nice-to-Haves

• Experience migrating legacy on-premise infrastructure and stored procedures to modern cloud data warehouses.
• Familiarity with workflow orchestration tools like Apache Airflow or Prefect.
• Hands-on experience with dbt (data build tool) for in-warehouse transformations.

Overview

We are seeking a versatile Full-Stack Cloud Developer to build modern front-end Web UIs for client data presentations. In this role, you will lead the development of our internal customer interface while also functioning as a billable resource for diverse client projects. You must be agile and capable of translating complex application data logs and cloud metrics into clean, actionable dashboards. This is a client-facing position that requires strong English and presentation skills. You will be expected to interface directly with clients on special projects, presentations, and requirements gathering.

Key Responsibilities

Build modern front-end Web UIs: Design client data presentations using APIs and application data logs for both internal and external clients.

Data Visualization: Integrate observability tools like Grafana to deliver high-fidelity metrics for cloud and NOC performance tracking.

Full-Stack Development: Develop secure, multi-tenant application logic hosted in AWS and Azure environments.

Enforce Version Control: Maintain strict discipline using GitHub for all code and Terraform for infrastructure deployments.

Client Engagement: Lead presentations regarding custom-built data solutions and portal features to stakeholders.

Rigorous Documentation: Maintain detailed records of architecture, API schemas, and codebase standards for long-term maintainability. Collaborative Execution: Work within an engineering team to ensure technical goals are met and operational friction is reduced.

Required Qualifications

Full-Stack Proficiency: Expert knowledge of modern frameworks (React, Node.js, or Python) to build data-driven applications. Observability & Metrics: Strong experience with Grafana integration, embedding dashboards, and visualizing FinOps/NOC data. Documentation Discipline: Proven ability to create clear technical guides for both team members and clients.

Communication: Exceptional verbal and written English skills for high-level client presentations and engagements.

Cloud Foundations: Hands-on experience with AWS and Azure services, particularly serverless (Lambda/Azure Functions).

Tooling: Proficient with GitHub and Terraform for version control and infrastructure management.

Professional Growth & Career Path

Technical Leadership: Opportunity to own the full lifecycle of mission-critical products and grow into Lead Architect roles. Certification Support: We encourage and support growing into advanced professional-level certifications to stay ahead of the curve.

Team Culture: Participate in a culture that values collective problem-solving, mentorship, and shared technical goals.

About the Internship

Nexora Group is seeking motivated and analytical students who are passionate about Data Science, Artificial Intelligence, and Machine Learning. This internship offers hands-on experience working with real-world datasets, AI-driven technologies, predictive analytics, and data visualization techniques.

Interns will gain practical exposure to data analysis workflows, AI-powered solutions, and industry-oriented projects while developing skills that are highly valued in today's technology landscape. Nexora Group focuses on innovation and technology-driven solutions across AI, digital experiences, and emerging technologies.

Key Responsibilities

• Collect, clean, and analyze structured and unstructured datasets.
• Perform Exploratory Data Analysis (EDA) to identify trends and patterns.
• Develop and evaluate Machine Learning models.
• Work with AI and Generative AI tools for data-driven solutions.
• Create dashboards, reports, and visualizations.
• Assist in predictive analytics and business intelligence projects.
• Document findings and present insights to mentors.
• Collaborate with team members on real-world projects.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Data Science and Machine Learning concepts.
• Familiarity with Pandas, NumPy, and data visualization libraries.
• Basic understanding of statistics and data analysis.
• Knowledge of SQL is a plus.
• Strong analytical and problem-solving abilities.
• Passion for Artificial Intelligence and emerging technologies.

Eligibility

• B.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
• Students pursuing Data Science, Computer Science, AI, IT, Mathematics, Statistics, or related fields.
• Freshers and recent graduates are encouraged to apply.

What You Will Learn

✅ Data Analysis & Visualization

✅ Machine Learning Fundamentals

✅ Artificial Intelligence Applications

✅ Generative AI Tools & Techniques

✅ Predictive Analytics

✅ Business Intelligence Concepts

✅ Industry-Oriented Project Development

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on Industry Project Experience

✅ Professional Mentorship & Guidance

✅ Resume & LinkedIn Profile Enhancement

✅ Portfolio Development Support

✅ Exposure to AI & Data-Driven Technologies

About the Internship

LetsIntern is offering an exciting opportunity for students passionate about Bioinformatics, Computational Biology, Genomics, and Biotechnology. This internship is designed to provide practical exposure to biological data analysis, genomic research, bioinformatics tools, and modern computational techniques used in the life sciences industry.

Interns will work on industry-oriented projects, gain hands-on experience with bioinformatics workflows, and develop valuable skills that are highly sought after in biotechnology, healthcare, pharmaceutical, and research organizations.

Key Responsibilities

• Assist in the analysis and interpretation of biological datasets.
• Work with genomic, proteomic, and sequence-based data.
• Perform literature reviews and scientific research.
• Learn and apply bioinformatics tools and databases.
• Support data collection, cleaning, and organization activities.
• Prepare reports, presentations, and project documentation.
• Collaborate with mentors and team members on assigned tasks.
• Participate in training sessions and project discussions.

Required Skills

• Basic understanding of Biotechnology, Bioinformatics, Genetics, or Molecular Biology.
• Interest in biological data analysis and computational biology.
• Familiarity with biological databases and research methods is a plus.
• Basic knowledge of Python, R, or data analysis tools is beneficial but not mandatory.
• Strong analytical and problem-solving skills.
• Good communication and documentation abilities.

Eligibility

• B.Sc., M.Sc., B.Tech, M.Tech, B.Pharm, M.Pharm, or related Life Science disciplines.
• Students pursuing Biotechnology, Bioinformatics, Genetics, Genomics, Microbiology, Computational Biology, Biochemistry, or related fields.
• Freshers and recent graduates are welcome to apply.

What You Will Learn

✅ Bioinformatics Fundamentals

✅ Genomics & Sequence Analysis

✅ Biological Databases & Research Tools

✅ Computational Biology Concepts

✅ Data Analysis in Life Sciences

✅ Scientific Research Methodologies

✅ Industry-Oriented Project Experience

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on Project Experience

✅ Mentorship from Industry Professionals

✅ Resume & LinkedIn Profile Enhancement

✅ Opportunity to Build a Professional Portfolio

✅ Exposure to Emerging Trends in Bioinformatics and Genomics

About Marseer AI

Marseer AI (www.marseerai.com) is a Seattle-based company building an AI-powered marketing intelligence platform for DTC and retail e-commerce brands. The platform combines brand strategy, customer data, automation, and generative AI to help marketing teams drive consistent, data-driven engagement across email, SMS, paid media, SEO, and affiliate channels.

Role Overview

We are looking for an experienced AI Engineer - Full Stack Developer to join the Marseer platform team. This is a dual-track role: you will build and maintain AI agent pipelines, LLM integrations, and RAG-based intelligence systems on the backend, while also owning frontend interfaces that surface insights, recommendations, and campaign outputs to marketing teams and brand operators.

You should be equally comfortable designing multi-step agentic workflows in Python and building clean, responsive product interfaces in React/Next.js. You understand how LLMs behave in production, know how to engineer prompts and tool chains for reliability, and care deeply about the end-to-end user experience.

What You Will Do

- Design and implement multi-step AI agent workflows using LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar.

- Build and maintain RAG pipelines, including chunking strategies, embedding generation, vector store management, and retrieval tuning.

- Integrate with LLM providers such as OpenAI, Anthropic, or others, including prompt engineering, tool/function calling, structured output generation, and context window management.

- Develop AI-driven features such as campaign brief generation, audience recommendations, content variant creation, and performance insight summarization.

- Implement evaluation and observability frameworks to monitor LLM output quality, latency, and cost in production.

- Build frontend interfaces using React and Next.js, including dashboards, agent interaction UIs, campaign builders, and insight surfaces.

- Design and implement RESTful and/or GraphQL APIs in Python (FastAPI or Flask) or Node.js to serve AI outputs to the frontend.

- Integrate frontend with backend AI services, streaming LLM responses, and real-time status updates.

- Work with structured and unstructured marketing data, campaign performance metrics, audience segments, content libraries, and brand strategy documents.

- Integrate with marketing platforms and data sources such as Klaviyo, Google Ads, Meta, and Shopify.

Requirements

- 5-10 years of professional software engineering experience, with meaningful time in both backend and frontend development.

- Proven experience building and deploying LLM-powered applications in production, not just prototypes.

- Strong proficiency in Python for backend and AI development.

- Strong proficiency in React and Next.js for frontend development.

- Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or equivalent.

- Experience building RAG pipelines, vector stores such as Pinecone, Weaviate, pgvector, or similar, embedding models, and retrieval strategies.

- Experience with API design, REST or GraphQL, and backend service architecture.

Strongly Preferred

- Experience designing and building multi-agent or agentic AI systems with tool use, memory, and planning capabilities.

- Familiarity with prompt engineering best practices, structured output generation, and LLM evaluation methodologies.

- Experience with streaming LLM responses and real-time UI updates using SSE or WebSockets.

- Prior work in a SaaS product company shipping production features.

- Familiarity with marketing platforms, e-commerce data, or martech ecosystems.

Good to Have

- TypeScript and modern frontend tooling such as Tailwind CSS or shadcn/ui.

- Familiarity with Snowflake or other cloud data warehouses as data sources for AI pipelines.

- Experience with observability tools for LLM applications such as LangSmith, Helicone, Arize, or similar.

- Understanding of marketing concepts such as segmentation, campaign lifecycle, attribution, and content personalization.

What We Are Looking For

- Availability to work US business hours; overlap with US Eastern or Pacific timezone is required for client collaboration and team standups.

- Strong written and verbal English communication.

- Product sense and ownership mindset.

- Comfort with ambiguity in non-deterministic LLM-powered systems.

- Collaborative working style across engineering, design, and client-facing functions.

What We Offer

- Competitive compensation based on experience.

- Fully remote role; work from anywhere in India, with Hyderabad-based candidates preferred.

- High-impact work at the frontier of applied AI for marketing and e-commerce.

- Direct exposure to real brand problems, real data, and real production AI systems.

- A small, senior team where your architecture decisions matter and your contributions are visible.

Key Responsibilities

Backend Development

• Design, develop, and maintain scalable backend services using Rust, Python, and TypeScript.
• Build high-performance microservices and APIs for AI-driven products.
• Develop fault-tolerant, secure, and maintainable distributed systems.
• Design event-driven architectures and asynchronous processing pipelines.
• Implement caching, message queues, and database optimization strategies.

AI & Machine Learning Integration

• Build and maintain backend infrastructure supporting LLMs, Generative AI, RAG systems, and AI Agents.
• Integrate models from providers such as OpenAI, Anthropic, Gemini, and open-source LLMs.
• Develop vector search solutions using Pinecone, Weaviate, Qdrant, or similar technologies.
• Build AI workflows for content generation, summarization, sentiment analysis, and conversational intelligence.
• Optimize AI inference pipelines for performance and cost efficiency.

System Architecture

• Design scalable architectures capable of handling high traffic and large volumes of data.
• Develop real-time processing systems and data pipelines.
• Implement observability, monitoring, logging, and alerting mechanisms.
• Drive performance tuning and latency optimization across services.

Cloud & DevOps

• Deploy and manage applications on AWS, GCP, or Azure.
• Work with Docker, Kubernetes, CI/CD pipelines, and Infrastructure as Code.
• Ensure system reliability, security, and scalability. 

Role Overview

The Senior AI/ Machine Learning Engineer will design, build, and optimise the core intelligence layer that powers Cliply’s video understanding and content analysis platform.

This role blends deep hands-on engineering with architectural ownership. You will work across video, audio, and text modalities, shaping model design while also delivering production-ready ML systems. You will be the technical anchor for Cliply’s AI stack, partnering closely with the Lead Architect and the engineering team to bring research concepts into scalable, real-world systems.

Key Responsibilities

Multimodal & Video ML Architecture

• Design and validate deep learning architectures for video, audio, and text understanding, including temporal modelling and multimodal fusion.
• Define approaches for long-sequence modelling, representation learning, and sequence-to-sequence tasks.
• Lead experiments with transformers, vision transformers, video encoders, and hybrid multimodal architectures.

Model Development & Optimisation

• Build and optimise models for content understanding, highlight detection, ranking, and scoring.
• Implement training pipelines, data loaders, augmentations, and evaluation metrics for large-scale video datasets.
• Optimize models for latency, throughput, and GPU efficiency using techniques such as quantization, pruning, distillation, batching, and ONNX/TensorRT.

Production ML Engineering

• Convert prototypes into robust, production-ready services.
• Collaborate with backend engineers to deploy models via scalable APIs and micro-services.
• Monitor model performance in production and design retraining loops for continuous improvement.

Technical Leadership

• Establish best practices for experimentation, evaluation, documentation, and reproducibility.
• Provide mentorship to junior engineers and contribute to Cliply’s long-term AI roadmap.
• Influence architectural decisions across the AI stack to ensure scalability and reliability.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
• 5–10+ years of experience as an ML Engineer, Applied Scientist, or similar role.
• Strong proficiency in PyTorch or TensorFlow, with hands-on experience training deep learning models.
• Deep expertise in multimodal video machine learning,
• Expertise in at least two of the following:

1. Video understanding / video ML
2. Computer vision
3. Speech/audio processing
4. Natural language processing
5. Multimodal fusion

• Experience with GPU training, distributed training, and large-scale datasets.
• Strong understanding of model optimization (quantization, pruning, distillation, ONNX/TensorRT).
• Solid software engineering fundamentals (Python, version control, testing, code review).

Preferred Qualifications

• Experience with multimodal architectures (video-text, audio-text, cross-modal transformers).
• Experience with MLOps tooling (MLflow, Weights & Biases).
• Prior work in startup environments or fast-paced product teams.
• Contributions to open-source ML projects or competitive ML experience (e.g., Kaggle).

Why Join Cliply

• Build the core intelligence layer of a next-generation video understanding platform.
• Own end-to-end architecture and model design - your work becomes the product.
• Work with a founder-led team that values technical excellence, autonomy, and speed.
• Shape the future of multimodal AI in a real product used by creators and enterprises.

Hiring for Azure Data Lead

Exp : 12 - 16 yrs

Edu : BE/B.tech

Permanent Remote

Notice period : Immediate - 15 days

Skills :

Microsoft Fabric (OneLake, Lakehouse, Warehouse)

Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Gen2, Delta Lake / Medallion Architecture

Power BI (Semantic layer, DAX)

Databricks SQL & T-SQL, PySpark / Python

Data Modelling (Star/Snowflake)CI/CD & DevOps for Data (Git, Pipelines)

8+ years data engineering / 3+ as leadTechnical leadership & stakeholder management

QC Engineer

Company Summary :

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com

Business Summary :

The Deltek Engineering and Technology team builds best-in-class solutions to delight customers and meet their business needs. We are laser-focused on software design, development, innovation and quality. Our team of experts has the talent, skills and values to deliver products and services that are easy to use, reliable, sustainable and competitive. If you're looking for a safe environment where ideas are welcome, growth is supported and questions are encouraged – consider joining us as we explore the limitless opportunities of the software industry.

Position Responsibilities :

Position Overview

As an Automation Engineer at Deltek, you will design, develop, and maintain automated test frameworks that ensure the quality and reliability of our software products. You will play a key role in accelerating delivery cycles by building scalable automation solutions that support our engineering teams in delivering exceptional software to project-based businesses worldwide.

Key Responsibilities

• Design, develop, and maintain automated test scripts using tools such as Selenium, Playwright, or equivalent frameworks
• Write clean, maintainable code in at least one programming language (e.g., JavaScript, Python, Java, or C#)
• Develop and enhance scripting solutions to support continuous integration and continuous delivery (CI/CD) pipelines
• Collaborate with developers, QA engineers, and product teams to identify automation opportunities and define test strategies
• Analyze test results, identify defects, and work with development teams to drive resolution
• Maintain and improve existing automation frameworks to increase coverage and efficiency
• Participate in code reviews and contribute to best practices in test automation
• Leverage AI-assisted testing tools and intelligent test generation techniques to enhance automation coverage and efficiency
• Utilize AI/ML-based anomaly detection and predictive analytics to proactively identify quality risks in the software delivery pipeline

Qualifications :

Required Qualifications

• 3–4 years of hands-on experience in test automation engineering
• Proficiency in at least one scripting or programming language (e.g., JavaScript, Python, Java, or C#)
• Hands-on experience with automation frameworks such as Selenium, Playwright, or similar tools
• Solid understanding of software testing methodologies and QA best practices
• Experience working within CI/CD environments and version control systems (e.g., Git)
• Strong analytical and problem-solving skills with attention to detail
• Familiarity with AI-powered testing tools (e.g., Testim, Mabl, Applitools) or experience integrating AI capabilities into test automation workflows

Preferred Qualifications

• Experience with API testing tools (e.g., Postman, REST Assured)
• Familiarity with cloud-based testing environments or containerization tools (e.g., Docker, Kubernetes)
• Knowledge of Agile/Scrum development methodologies
• Experience with performance or load testing tools
• ISTQB or equivalent testing certification
• Experience using large language models (LLMs) or generative AI tools (e.g., GitHub Copilot, ChatGPT) to accelerate test script development and documentation
• Understanding of machine learning concepts as applied to test data generation, defect prediction, or intelligent test prioritization

Description:

-> Work on full-stack development projects, handling both front-end and back-end development tasks.

-> Gain practical experience in designing, developing and deploying scalable web and application solutions.

-> Collaborate with teams to build efficient, secure, and user-friendly applications using modern technologies.

-> Work with a wide range of technologies and domains, including:

  Java Application Programming

  Web Development

  Python Application Programming with Django

  Machine Learning

  Data Science

  Artificial Intelligence

  Cyber Security

  Data Analytics

-> Develop problem-solving, analytical, and technical skills by working on projects.

Duration: 1 - 6 months

Mode: Online/Offline

Eligibility: Any BCA/MCA pursuing Students can apply.

Perks:

-> Internship Certificate

-> Letter of Recommendation.

Description:

-> Work on full-stack development projects, handling both front-end and back-end development tasks.

-> Gain practical experience in designing, developing and deploying scalable web and application solutions.

-> Collaborate with teams to build efficient, secure, and user-friendly applications using modern technologies.

-> Work with a wide range of technologies and domains, including:

  Java Application Programming

  Web Development

  Python Application Programming with Django

  Machine Learning

  Data Science

  Artificial Intelligence

  Cyber Security

  Data Analytics

-> Develop problem-solving, analytical, and technical skills by working on projects.

Duration: 1 - 6 months

Mode: Online/Offline

Eligibility: Any BE/BTech pursuing Students can apply.

Perks:

-> Internship Certificate

-> Letter of Recommendation.

Senior AI Engineer — Ruby on Rails

Techjays · Coimbatore / Chennai · Hybrid · Immediate – 30 Days Notice

About Techjays

We're the AI Reimagination Company — and that's not a tagline we put on a deck. It's what we actually do.

Techjays helps global enterprises rebuild the way they operate using AI at the core: not as a pilot, not as a feature, but as a foundational layer across products, workflows, and infrastructure. We're an Anthropic partner, which means our engineers get early access to frontier models and tools before they hit the market.

Our team includes engineers and leaders from Google, Akamai, NetApp, ADP, Cognizant Consulting, and Capgemini. We run like a high-agency startup, but we build production systems that real enterprise clients depend on.

Every project is greenfield. Every line of code you write ships.

What This Role Actually Is

This isn't a "keep the monolith alive" job.

You'll be designing and building new AI-powered features, integrating LLM APIs into production Rails applications, and using Claude Code as a core part of your daily workflow — not as an experiment. You'll work directly with US-based enterprise clients alongside Product Managers, AI Business Consultants, and Delivery Excellence Managers.

Your architecture decisions will have visible business impact.

What You'll Own

• Design, build, and maintain production-grade Ruby on Rails applications for US enterprise clients — from architecture to deployment
• Integrate LLM APIs (Claude, GPT-4, Gemini) into the Rails stack, building AI-powered features that drive real business outcomes
• Use Claude Code daily as your AI development partner — for generation, debugging, documentation, and velocity
• Build responsive, performant React front-ends from wireframes and design specs
• Own RESTful and GraphQL API design for client applications and third-party integrations
• Drive database design and optimisation — schema, queries, indexing, and migrations on PostgreSQL/MySQL
• Lead code reviews and raise the technical bar through constructive feedback
• Document architecture decisions, API contracts, and implementation patterns

Must-Haves

• 6+ years of deep, production-grade Ruby on Rails experience — advanced framework patterns, background jobs (Sidekiq/Redis), design patterns, best practices
• Hands-on experience with Claude Code (Anthropic) for AI-assisted development — this is central to how we build
• Strong React skills — hooks, component architecture, state management, wireframe to production
• Expert-level PostgreSQL/MySQL — schema design, query optimisation, indexing, performance tuning
• Proven experience designing RESTful and GraphQL APIs at scale
• Experience integrating third-party LLM APIs (OpenAI, Anthropic, Google Gemini) into production Rails apps
• Strong software architecture fundamentals — MVC, service objects, design patterns, testability
• Deep comfort with Git, Gitflow, and PR-based collaboration workflows

Good to Have

• Python for scripting, automation, or backend service integration alongside Rails
• AWS familiarity — EC2, S3, RDS, Lambda — for deployment and infrastructure
• MongoDB or NoSQL in polyglot persistence architectures
• Vector databases (Pinecone, pgvector, Weaviate) for LLM application development
• LangChain, LangGraph, or similar orchestration frameworks for AI agents
• SaaS multi-tenancy patterns and high-traffic web application experience
• Open source contributions or a strong public GitHub profile

Why Join Techjays

• Claude Code is standard practice here, not a side experiment — you'll use it every day to ship faster and smarter
• Anthropic partner access — early visibility into frontier AI tools and capabilities before the market sees them
• Greenfield only — you'll design architecture, not inherit technical debt
• Global client exposure — your engineering decisions translate directly to measurable business outcomes for US enterprise clients
• Team pedigree — you'll learn alongside engineers who've shipped at real scale at Google, Akamai, and NetApp
• AI is the product here, not a feature. You'll spend your career at the intersection of software engineering and AI systems

What We're Looking For Beyond the Resume

• Builder mindset — you think in systems, not tickets
• Ownership — you take features from idea to production
• Structured thinking in ambiguous, fast-moving environments
• Clear communicator, collaborative team player

What We Offer

• Competitive compensation
• Hybrid work — Coimbatore office or remote flexibility
• Paid holidays and flexible time off
• Medical insurance for self and family (up to ₹4 Lakhs per person)
• Opportunity to work on production-grade AI systems for global clients
• A culture built on clarity, integrity, and continuous growth

Location: Coimbatore / Chennai — Hybrid Notice Period: Immediate to 30 days preferred

Job Title: Senior Software Development Engineer in Test (SDET)

Location: Bangalore

Experience: 3–6 Years

Employment Type: Contract (3 Months)

About the Role:

We are looking for a skilled and passionate Senior Software Development Engineer in Test (SDET) to join our team on a 3-month contract. The ideal candidate will have a strong software development background combined with expertise in test automation, quality engineering, and modern software development practices. You will play a key role in building scalable automation frameworks, driving quality initiatives, and ensuring the reliability and performance of our applications.

Key Responsibilities:

• Design, develop, and maintain robust and scalable test automation frameworks from scratch.
• Define and implement automation strategies across multiple applications and services.
• Create and execute automated test scripts for web applications, APIs, and backend services.
• Collaborate with developers, architects, product managers, and QA teams to ensure quality throughout the software development lifecycle.
• Perform API testing, backend validation, and end-to-end testing across distributed systems.
• Identify, troubleshoot, and resolve defects across various application layers.
• Integrate automated tests into CI/CD pipelines to enable continuous testing.
• Conduct code reviews and mentor team members on automation best practices.
• Drive improvements in test coverage, reliability, and engineering efficiency.
• Participate in Agile ceremonies and contribute to release planning and quality assurance strategies.

Required Skills & Qualifications:

• 3–6 years of experience in Software Testing, Test Automation, or SDET roles.
• Strong programming skills in at least one of the following languages: Java, Python, JavaScript, or C#.
• Solid understanding of Data Structures, Algorithms, and Object-Oriented Programming (OOP) concepts.
• Proven experience in designing and building automation frameworks from scratch.
• Strong knowledge of software design principles, design patterns, and clean coding practices.
• Hands-on experience with API testing and backend validation.
• Familiarity with Microservices Architecture and distributed systems.
• Experience with Git and collaborative development workflows.
• Experience integrating automated tests within CI/CD pipelines.
• Strong debugging, analytical, and problem-solving skills.
• Ability to work independently and drive quality initiatives with minimal supervision.

Preferred Qualifications:

• Exposure to Docker and containerized environments.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of performance, security, or reliability testing is an added advantage.

Contract Details

• Duration: 3 Months
• Location: Bangalore (Onsite/Hybrid as per project requirements)

Job Title : DBA – AWS Aurora PostgreSQL

Experience : 6+ Years

Work Mode : Remote

Laptop Pickup : One-time pickup from Noida, Bengaluru, Pune, Hyderabad, or Chennai

Contract Duration : 6 Months

Job Summary :

We are seeking an experienced AWS Aurora PostgreSQL DBA to manage, optimize, and support enterprise database environments hosted on AWS.

The ideal candidate should have strong expertise in PostgreSQL, AWS RDS/Aurora PostgreSQL, database performance tuning, high availability, disaster recovery, security, and production support.

Key Skills Required :

AWS Aurora PostgreSQL, PostgreSQL DBA, AWS RDS, SQL Performance Tuning, Query Optimization, Indexing, Execution Plan Analysis, High Availability (HA), Disaster Recovery (DR), Multi-AZ, Read Replicas, CloudWatch, Aurora Performance Insights, Backup & Recovery, Database Security, IAM, Audit Logging, Production Support, RCA, Python/Shell/PowerShell Scripting, Terraform/CloudFormation, AWS DMS, CI/CD, Git.

Mandatory Skills :

• 4 to 5+ years of experience in PostgreSQL Database Administration.
• 3 to 5+ years of hands-on experience with AWS RDS and Aurora PostgreSQL.
• Strong SQL expertise, including query optimization, indexing, and execution plan analysis.
• Experience with Aurora clustering, Multi-AZ deployments, read replicas, failover management, backup, and recovery.
• Hands-on experience with AWS CloudWatch and Aurora Performance Insights.
• Strong understanding of database security, encryption, IAM controls, audit logging, and compliance practices.
• Experience in production support, incident management, troubleshooting, and root cause analysis (RCA).
• Scripting/automation experience using Python, Shell Script, or PowerShell.
• Experience with Infrastructure as Code (Terraform or CloudFormation).
• Knowledge of AWS DMS, DevOps practices, CI/CD pipelines, and Git.

Preferred Skills :

• Experience supporting Master Data Governance (MDG) or enterprise data platforms.
• Experience working in healthcare or other highly regulated environments.
• Exposure to AWS services such as Redshift, DynamoDB, and S3.
• AWS Certified Database Specialty or AWS Solutions Architect certification is preferred.

Key Responsibilities :

• Manage and support AWS Aurora PostgreSQL environments, including provisioning, configuration, monitoring, scaling, and maintenance.
• Optimize database performance through query tuning, indexing, and proactive monitoring.
• Implement and maintain high availability, backup, recovery, and disaster recovery solutions.
• Troubleshoot production issues, perform root cause analysis, and ensure database reliability and availability.
• Collaborate with application, cloud, and data engineering teams to support deployments and production releases.
• Automate routine DBA activities and improve operational efficiency using scripting and AWS-native tools.

Qualifications :

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Strong analytical, troubleshooting, and communication skills.
• Ability to work independently and manage multiple priorities in a fast-paced environment.

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

Job Title:  Sr. AI Ops Engineer

Experience: 8+ Years

Location: Remote

We’re looking for a hands-on Lead AI Ops Engineer to drive AI-powered automation across enterprise infrastructure. This role involves working closely with senior stakeholders to identify opportunities and implement Agentic / AIOps solutions at scale.

 What You’ll Do

• Identify automation opportunities across Cloud & Enterprise Infrastructure
• Design & build AI/Agentic solutions aligned with AIOps frameworks
• Collaborate with Principal Engineers / Directors on high-impact initiatives
• Own end-to-end delivery: Problem → Solution → Deployment

 Tech Stack

• Must: Python
• Good to have: JavaScript, Java, Scala, R
• AI/ML: Databricks, MLflow
• Frameworks: LangChain, LangGraph, LLaMA, Cohere, DBRX
• Cloud: AWS, Azure, GCP
• Others (Plus): Google ADK, MCP, A2A, Argo

 Ideal Profile

• Strong engineering maturity & ownership
• Experience in AI-driven automation / AIOps
• Ability to work directly with senior technical stakeholders

 Why Apply?

Work on cutting-edge AI Ops & Agentic automation in a large-scale enterprise environment with high visibility.

Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)

Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.

Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.

Mandatory (Experience 3) – Must have hands-on experience architecting production generative AI applications — LLM integrations, vector databases, RAG systems, and evaluation pipelines

Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.

Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).

Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.

Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.

Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them

About AGI Ready

We're an AI-native development studio. We don't build "websites" — we build agents, automations, and custom products for clients who need real software shipped fast. Our stack is modern (Next.js, TypeScript, Claude Code), our pace is high, and our philosophy is simple: 60% with AI beats 0% without.

We're a small team scaling deliberately. This is an early hire, which means real ownership, real impact, and a front-row seat to building the agency from the inside.

The Role

You'll be a core builder. That means owning features end-to-end — from understanding what the client needs, to architecting it, to shipping production code, to fixing it when it breaks. You won't be handed perfect tickets. You'll be handed problems, and you'll be trusted to solve them.

You'll work primarily with AI coding tools (Claude Code, Codex) as your daily drivers. We're looking for someone who has moved past "AI writes my code for me" and into vibe engineering — using AI as a thought partner and force multiplier while still owning architecture, judgment, and quality.

What You'll Do

• Build and ship full-stack features using Next.js, TypeScript, and Node.js
• Architect and integrate APIs (third-party services, AI APIs, webhooks, async workflows)
• Use Claude Code and Codex to move fast without sacrificing quality
• Debug, deploy, and own production — not just write code and walk away
• Break complex problems into smaller, manageable pieces and ship iteratively
• Work directly with the founder and a tight team on multiple client products

What We're Looking For

Must-haves

• 1+ year of hands-on experience at a real product startup (shipping, not just learning)
• Strong with Next.js, TypeScript, and Node.js
• Comfortable using Claude Code and Codex as primary development tools
• Real vibe engineering experience — you direct AI, you don't just copy-paste from it
• Solid grasp of API integrations, webhooks, and async processing
• Can debug AI-generated codebases and take them to production

Preferred

• 3–5 years of product/startup experience
• Experience with managed services (Supabase, Clerk, etc.) over building everything from scratch
• Exposure to building agents or AI workflows (MCP, OpenAI APIs, agentic frameworks)

Who Thrives Here

We hire for trajectory, not credentials. The people who do well at AGI Ready tend to be:

• Frugal — you hack solutions together with what's available instead of waiting for perfect conditions
• Transformation-driven — show us your last two years, not your degree. We care where you've come from and how fast you climb
• Self-driven builders — you've taught yourself skills nobody handed you, and you ship things because you can't help it
• Assembly-minded — your first instinct is "who's already solved this?" not "let me build it from scratch"
• In it for the long run — we're looking for people to grow with, not churn through

How to Apply

Send us:

1. Your GitHub or portfolio
2. One thing you built that nobody asked you to build
3. A short note on a hard technical problem you solved — and how you used AI to solve it

Full Stack Engineer – Spacetil

About Spacetil

Spacetil is a modern financial operations and accounting automation platform that helps businesses streamline bookkeeping, banking integrations, transaction processing, reconciliations, and financial reporting. We are building scalable products that simplify complex financial workflows for customers across multiple geographies.

Role Overview

We are looking for a passionate Full Stack Engineer (1–3 years experience) to join our product engineering team. You will work across the entire technology stack to design, build, and maintain scalable web applications and backend services. This role offers the opportunity to contribute directly to product development, collaborate with cross-functional teams, and solve real-world business challenges.

Responsibilities

• Develop and maintain scalable web applications using modern frontend and backend technologies.
• Design and implement RESTful APIs and backend services.
• Build responsive and intuitive user interfaces using React.js and Tailwind CSS.
• Develop robust server-side applications using Java and Python.
• Write efficient SQL queries and optimize database performance.
• Collaborate with product managers, designers, and fellow engineers to deliver high-quality features.
• Participate in code reviews and contribute to engineering best practices.
• Troubleshoot, debug, and resolve production issues.
• Continuously improve application performance, security, and reliability.

Required Skills

• 1–3 years of experience in full-stack software development.
• Strong proficiency in Java and/or Python.
• Experience with React.js and modern frontend development.
• Good understanding of SQL and relational databases.
• Experience with Tailwind CSS for responsive UI development.
• Understanding of REST APIs, authentication, and web application architecture.
• Familiarity with Git and collaborative development workflows.
• Strong problem-solving and analytical skills.

Preferred Qualifications

• Experience with Spring Boot, PostgreSQL, or similar frameworks/databases.
• Exposure to cloud platforms (AWS, Azure).
• Knowledge of CI/CD pipelines and DevOps practices.
• Experience working with financial, accounting, or fintech products is a plus.

What We Offer

• Opportunity to work on a fast-growing fintech platform.
• Flexible remote-first work environment.
• Ownership of impactful projects and features.
• Collaborative and learning-focused engineering culture.
• Competitive compensation and career growth opportunities.

Location: Remote

Experience: 1–3 Years

Employment Type: Full-Time / Contractual

Skills: Java, Python, SQL, React.js, Tailwind CSS

Join Spacetil and help build the next generation of financial automation solutions.

Key Responsibilities

• Design, develop, test, and maintain PHP-based web applications and APIs.
• Build and enhance features for our SaaS platform with a focus on performance, scalability, and security.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Write clean, maintainable, and well-documented code following best practices.
• Optimize application performance and troubleshoot production issues.
• Integrate third-party services, APIs, and payment gateways as required.
• Participate in code reviews and contribute to improving development processes.
• Work with databases to design efficient schemas, write optimized queries, and ensure data integrity.
• Assist in deployment, monitoring, and ongoing maintenance of applications.

About the Role

Viamagus is a fully AI-driven engineering organization.

We're hiring a Technical Architect who has built real systems, deployed them to production, and meaningfully integrated AI into their engineering practice. You'll lead architecture across all client engagements.

Must-Have: Engineering Foundation

• Bachelor's in CS/Engineering or related field (Master's preferred)
• 8+ years of software development, 3+ years in an architect/lead role
• Built systems from scratch and taken them to production - owned the full lifecycle, not just slices
• Multiple integration experiences - third-party APIs, enterprise systems (SAP, Salesforce, ERP), messaging/event buses, legacy modernization
• Built frameworks for scalability - reusable platforms, SDKs, shared libraries, and internal developer tooling adopted across teams
• Technology-agnostic strength - strong across at least one modern backend stack, one frontend framework, and one cloud platform; able to pick the right tool for the job rather than defaulting to favourite
• AWS or Azure cloud architecture - VPC design, IAM, container orchestration, cost optimization
• DevOps fluency: Docker, Jenkins/GitHub Actions, IaC (Terraform/CDK)
• Performance tuning, distributed tracing, structured logging, APM tools (Datadog, New Relic, or equivalent)
• AppSec collaboration - OWASP Top 10, VAPT remediation, secrets management, compliance (ISO/SOC 2/HIPAA exposure a plus)

Must-Have: AI-Era Awareness

You will be expected to architect systems that use AI effectively and lead engineers who do the same. Working knowledge of several of these is required:

• AI-assisted development - daily driver of Claude Code, Cursor, Copilot, or equivalent; can articulate where they help, where they fail, and how to get better outcomes from them
• LLM integration patterns - understanding of when to use OpenAI, Anthropic, Gemini, or open-source models; familiarity with API usage, streaming, function calling, structured outputs
• RAG basics — vector DBs (pgvector, Pinecone, Qdrant), embeddings, chunking, retrieval tradeoffs — enough to review and guide RAG implementations
• Agentic systems awareness — conceptual understanding of tool use, multi-step agents, and frameworks like LangGraph or CrewAI
• MCP (Model Context Protocol) — awareness of what it is and where it fits
• Prompt engineering fundamentals — versioning prompts, structured outputs, guardrails, handling hallucinations
• AI evaluation and cost awareness — how to measure quality, latency, and cost of LLM-powered features
• Curiosity and experimentation mindset — has tried things beyond ChatGPT in a browser tab

Responsibilities

Architecture & Delivery

• Design scalable, secure architectures for client engagements
• Lead technical due diligence on proposals - feasibility, effort estimation, risk flagging
• Drive production readiness: incident management, observability, release processes
• Review and approve high-impact design decisions across projects

Team & Stakeholders

• Mentor 15–20 engineers across backend, mobile, and cloud teams
• Conduct architecture reviews, code reviews, and technical retrospectives
• Engage directly with client CTOs/architects on solution design and technical escalations
• Translate business objectives into architectural decisions and vice versa

Quality, Risk, Compliance

• Enforce security-first design - threat modelling, data classification, AI-specific risks (prompt injection, PII leakage, model supply chain)
• Ensure compliance readiness for ISO 27001, SOC 2, HIPAA, where applicable
• Identify and mitigate delivery risks early; escalate with proposed mitigations

Nice to Have

• Contributions to open-source projects or AI tooling
• Experience with real-time sync (CRDTs, Realm, Ditto) or offline-first architectures
• Published technical content - blogs, talks, GitHub
• Google/AWS/Azure certifications (bonus, not substitute)

Job Title: Digital Automation Engineer 

Experience: 3+ Years

Location: Remote

Role Summary

We are looking for an Automation Engineer to design and build solutions that eliminate manual tasks within production support operations. This role is primarily focused on automation engineering, with secondary exposure to production support. The ideal candidate will also have hands-on experience with AWS, CI/CD pipelines, and Slack integrations to support modern automation and DevOps-driven workflows.

Key Responsibilities

• Build and deploy automation solutions using Python/Java/Node.js or RPA tools
• Automate monitoring, alerts, reporting, and reconciliation processes
• Integrate systems via REST APIs, database connections, and file-based workflows
• Identify and optimize manual support processes through automation
• Support L2/L3 production activities, including incident triage and RCA
• Work with monitoring tools such as Splunk and Grafana for log analytics and dashboarding
• Support releases, deployments, and environment-related activities
• Build and maintain CI/CD pipelines using tools like Git, Jenkins, GitHub Actions, or similar
• Develop AWS-based automation (Lambda, CloudWatch, S3, API Gateway, IAM workflows, etc.)
• Create automation workflows integrated with Slack for notifications, approvals, and operational triggers
• Collaborate with DevOps and Cloud teams to ensure scalable, secure automation design

Required Skills

• 3–5 years of experience in automation, scripting, or software engineering
• Strong coding skills in Python, Java, or JavaScript
• Hands-on experience with REST APIs, JSON, SQL
• Exposure to monitoring platforms like Splunk and Grafana
• Basic understanding of production support and ITIL processes
• Experience working with ServiceNow or other ITSM platforms (preferred)
• Practical experience working with AWS cloud services
• Experience building CI/CD pipelines using modern DevOps tools
• Experience implementing Slack integrations using bots, webhooks, or API-based workflows

Preferred Qualifications

• Experience with event-driven automation
• Exposure to containerization (Docker/Kubernetes)
• Knowledge of security best practices in automation and cloud workflows