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DATAECONOMY

Senior / Lead GenAi Engineer

Hyderabad, Telangana, India4 months ago

Senior / Lead GenAI Engineer

Job Type: Full time

Industry: IT Services

Location: Hyderabad / Pune

Experience Level: 8 - 15 years

Qualification: BTech / MTech / MCA

Mode of Work: Hybrid

About the Role

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, AgentCore, and modern 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, SageMaker, 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, AgentCore, Knowledge Bases, and Bedrock Guardrails for production GenAI applications.
  • Agentic AI development: proven experience building multi-agent systems and autonomous workflows using LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or AWS-native agent frameworks.
  • RAG pipeline design: end-to-end RAG implementation — vector databases (Pinecone, OpenSearch, 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, SageMaker, 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 environment.
  • 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.

About DATAECONOMY

DATAECONOMY is a data and AI consultancy that provides enterprise-grade solutions for data modernization, analytics, and artificial intelligence. The company serves financial services, banking, insurance, and other enterprises with services spanning data engineering, data governance, AI/ML, cloud enablement, and digital transformation.

Industry
IT Consulting and Outsourcing
Head office
Dublin, Ohio, United States
Company size
588
Founded
2018
Data EngineeringData AnalyticsData GovernanceArtificial Intelligence and Machine LearningCloud Platform ServicesData Platform ModernizationBusiness IntelligenceMLOpsGenerative AIDigital Transformation
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Senior / Lead GenAi Engineer