Job Title: Senior / Lead GenAI Engineer
Experience Level: 8 - 15 years
Location: Hyderabad / Pune

Qualification: BTech/MTech/MCA
Mode of Work: Hybrid

We are seeking a high-calibre Senior / Lead GenAI Engineer to architect, build, and lead the delivery of production-grade Generative AI and Agentic AI solutions within our Banking & Financial Services platform. You will combine deep hands-on engineering with technical leadership — guiding a team of GenAI engineers, contributing production-quality code, and partnering with Solution Architects and business stakeholders to bring cutting-edge AI capabilities into real financial products at scale.

Key Responsibilities:

- Lead a team of GenAI engineers — providing technical leadership, architecture guidance, mentoring, and code reviews to drive engineering excellence and delivery quality.

- Actively contribute production-quality code — this is a hands-on role; you will design, develop, and deploy GenAI solutions alongside the team, not just guide from the sidelines.

- Design and deploy production-grade GenAI and Agentic AI applications — secure, scalable, compliant, and aligned with BFSI regulatory requirements (RBI, SEBI, GDPR).

- Build AI agents and multi-agent workflows using Amazon Bedrock, Bedrock Agents, Agent Core, and contemporary agent orchestration frameworks — enabling autonomous, multi-step financial AI processes.

- Design and implement RAG-based solutions — including vector database integration, chunking strategies, retrieval optimisation, prompt engineering, AI guardrails, and model evaluation frameworks.

- Develop reusable frameworks, libraries, and accelerators — standardising GenAI engineering practices and improving delivery velocity across the team.

- Design and implement cloud-native solutions on AWS — using services such as Bedrock, Sage Maker, Lambda, S3,



and Infrastructure as Code (Terraform) for scalable, production-ready deployments.

- Collaborate with Solution Architects, Product Owners, and business stakeholders — translating complex BFSI requirements (fraud detection, risk analytics, compliance, customer engagement) into scalable GenAI solutions.

- Troubleshoot complex technical issues — from hallucination rates and retrieval quality to latency, cost optimisation, and production incidents — guiding teams through design and implementation challenges.

- Produce high-quality technical documentation — including architecture documents, HLDs, LLDs, API documentation, deployment guides, and operational runbooks for audit and knowledge sharing.

- Stay current with emerging AI technologies — evaluating new models, frameworks, and approaches; recommending improvements to architecture, engineering practices, and solution design.

Requirements

- Amazon Bedrock expertise: deep hands-on experience with Bedrock, Bedrock Agents, Agent Core, Knowledge Bases, and Bedrock Guardrails for production GenAI applications.

- Agentic AI development: proven experience building multi-agent systems and autonomous workflows using Lang Chain, Lang Graph, Llama Index, CrewAI, Auto Gen, or AWS-native agent frameworks.

- RAG pipeline design: end-to-end RAG implementation — vector databases (Pinecone, Open Search, Weaviate, pgvector), embedding models, retrieval strategies, and evaluation using RAGAS or equivalent.





- Prompt engineering mastery: advanced prompting techniques — few-shot, chain-of-thought, structured outputs, system prompt design, and prompt versioning for production systems.

- Python proficiency: production-grade Python for GenAI applications, API development (FastAPI), and integration with AWS services using Boto3.

- AWS cloud architecture: practical experience with AWS services — Bedrock, Sage Maker, Lambda, S3, DynamoDB, API Gateway, ECS/EKS — and Terraform for IaC.

- LLM evaluation and observability: model evaluation frameworks, A/B testing, hallucination monitoring, latency tracking, cost optimisation, and LLMOps practices in production.

- Technical leadership: proven track record leading engineering teams — architecture reviews, code reviews, mentoring, and driving delivery standards in an Agile workplace.

- BFSI domain understanding: familiarity with banking and financial services use cases — fraud detection, AML, credit risk, regulatory reporting, customer analytics, and compliance constraints (RBI, SEBI, GDPR).

Benefits

- Comprehensive Medical Coverage:
Health insurance of INR 5.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind.

- Robust Protection Plans:
Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones.

- Retirement Benefits:
PF and Gratuity provided as per standard government regulations.

- Flexible Work Options:
Enjoy hybrid work arrangements & flexible working hours

- Generous Leave Policy:
21 days of annual leave, in addition to 10 company-declared holidays.

- Employee Well-being Spaces:
Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.

📌 Senior / Lead GenAi Engineer (India)
🏢 DataEconomy
📍 India