Full Stack AI Engineer

Full Stack AI Engineer

Location: Bangalore (Work from Office)

Exp: 8\+ years

Only candidates ready to join immediately should apply.

Position Overview

Staff Full Stack AI Engineer to design, build, and scale reusable AI components and full stack solutions for enterprise applications, with an immediate focus on migrating existing work toward AI agent development. Strong hands\-on expertise in React/TypeScript/Angular, Python, and Java, plus GenAI fundamentals — RAG, AI Agents, AI Gateway integration, and MCP — with a platform mindset for reusable components over one\-off solutions.

Requirements

Experience

8\+ years Full Stack Development, including architecture\-level ownership; 2–3\+ years hands\-on AI/LLM implementation (RAG, agents, AI gateway integration, workflows) in production

Track record designing reusable components or shared libraries adopted by multiple teams — not just feature\-level delivery

Proven technical lead driving end\-to\-end delivery on complex AI/full stack initiatives — hands\-on and delivery\-focused

End\-to\-end delivery of enterprise\-grade applications, including chatbot implementations for business stakeholders

Agile/Scrum experience, including sprint planning and technical roadmap input

Required Technical Skills

Frontend (required): React.js, TypeScript, Angular

Backend (required): Python, Java, REST APIs, Microservices Architecture

AI \& GenAI: Azure OpenAI/OpenAI APIs, RAG, Vector Databases (e.g., Qdrant), AI Agents/Multi\-Agent Systems, LangChain, LangGraph, MCP, Prompt Engineering, Function Calling/Tool Use, Model Evaluation \& Monitoring, AI Gateway Integration (e.g., LiteLLM), Semantic Search

Databases: PostgreSQL, MSSQL, MongoDB, Elasticsearch/OpenSearch, Vector Databases; Cloud Databases (Azure SQL/Cosmos DB, AWS RDS/DynamoDB) — good to have

Security: OAuth2/OpenID Connect, API Security, Secure Coding, Secrets Management, AI Governance and Compliance

Responsibilities

Delivered as per project requirements — scope varies by initiative.

Build AI agents, AI\-driven workflows, RAG pipelines, and AI gateway integrations tailored to each project's requirements.

Develop migration of legacy applications to the latest tech stack using AI workflows and agent development for faster implementation.

Design and develop scalable enterprise web applications, APIs, and microservices across the full stack.

Own architecture decisions for AI\-powered applications, with a strong focus on security and credentials management.

Act as technical lead driving end\-to\-end delivery, resolving technical blockers, and shaping sprint planning and technical discussions with Product Owners, Architects, QA Engineers, and Business Stakeholders.

Build CI/CD pipelines and containerized deployments (Docker/Podman), including Linux server setup and administration.

Monitor AI quality, hallucinations, and cost/performance across deployed capabilities.

Nice\-to\-Have Skills

Next.js, Node.js, .NET/C\#, GraphQL, Material UI/Fluent UI, State Management (Redux, Zustand), Docker/Podman, GitHub Actions/Jenkins, CI/CD Pipelines, Linux administration and deployment/server setup, Kubernetes/OpenShift, Cloud platforms (Azure/AWS/GCP), Jest/Playwright, Pytest, AI observability/eval tooling (LangSmith, Langfuse, Arize), Semantic Kernel, CrewAI/AutoGen, Knowledge Graphs, Event\-driven architectures (Kafka), AI testing frameworks

Pay: ₹1,600,000\.00 \- ₹3,000,000\.00 per year

Benefits

• Flexible schedule

Work Location: In person