Lead Gen AI Full Stack Engineer

Open Position: GenAI Full-Stack Lead Engineer

Location: Baner, Pune (Hybrid)

Experience: 58 Years

Must-Have: React.js + Any Backend (Node.js / Python / Java / Golang / .NET) + AWS + LLM + NLP

Shift Time: 2:00 PM 11:00 PM (IST)

Notice Period: Immediate to 15 Days

Position Overview:

We are seeking a GenAI Full-Stack Lead Engineer with strong software engineering fundamentals and the ability to build production-grade frontend, backend, and GenAI-driven systems. The ideal candidate should have expertise in React, any modern backend technology, RAG pipelines, LLM APIs, Agentic AI architectures, and AWS cloud services. Prior FinTech experience is mandatory.

Key Responsibilities:1. Full-Stack Engineering:

• Build scalable user-facing applications using React, Next.js, or similar frontend frameworks.

• Develop backend services using Node.js, Python, Java, Golang, .NET, or any modern backend framework.

• Design and develop RESTful and/or GraphQL APIs.

• Implement secure authentication, authorization, and system integrations.

• Ensure high performance, scalability, reliability, and code quality across the application stack.

2. GenAI Systems & Agentic Architectures:

• Design and implement end-to-end RAG pipelines, including document ingestion, chunking, embeddings, vector indexing, and retrieval optimization.

• Integrate and orchestrate LLM APIs such as OpenAI, Anthropic Claude, AWS Bedrock, and similar foundation models.

• Build AI Agents and Agentic workflows for reasoning, tool execution, task orchestration, and autonomous decision-making.

• Develop reusable prompt frameworks, guardrails, caching, evaluation pipelines, and fallback mechanisms.

• Optimize AI systems for latency, accuracy, scalability, safety, and cost.

3. Cloud Engineering & DevOps:

• Deploy and manage applications on AWS using services such as Bedrock, Lambda, ECS/EKS, S3, API Gateway, DynamoDB, and RDS.

• Build CI/CD pipelines and automate deployments across staging and production environments.

• Implement monitoring, logging, tracing, and performance optimization.

• Work with vector databases including Pinecone, Weaviate, Chroma, or Milvus.

4. FinTech Product Development:

• Develop AI-powered features for financial products with a focus on security, compliance, and auditability.