DATAECONOMY

Technical Project Manager

• Lead end-to-end project management for data-driven initiatives, including planning, execution, delivery, and stakeholder communication.
• Work closely with data engineers, analysts, and software developers to ensure technical accuracy and timely delivery of projects.
• Translate business requirements into technical specifications and work plans.
• Manage project timelines, risks, resources, and dependencies using Agile, Scrum, or Kanban methodologies.
• Drive the development and maintenance of scalable ETL pipelines, data models, and data integration workflows.
• Oversee code reviews and ensure adherence to data engineering best practices.
• Provide hands-on support when necessary, in Python-based development or debugging.
• Collaborate with cross-functional teams including Product, Data Science, DevOps, and QA.
• Track project metrics and prepare progress reports for stakeholders.

AI Engineer

• 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.

Technical Project Manager

Senior/Lead GenAi Engineer