Engineering Manager - Generative AI

As Engineering Manager, you will lead engineering teams building enterprise-grade Generative AI solutions. You will drive the adoption of Large Language Models (LLMs) and agentic workflows to deliver process efficiencies, automation, simplification and risk reduction across business solutions. This is a hybrid role based in Bengaluru, combining hands-on technical direction with people leadership and stakeholder engagement.

Our client is a leading global financial services organisation with a strong presence in banking and technology. They are known for scale, innovation and a commitment to responsible, secure digital solutions that serve millions of customers. Their culture emphasises integrity, service, excellence and continuous learning.

Responsibilities

• Lead and grow high-performing engineering teams delivering Generative AI and agentic solutions within scope, time and budget
• Oversee delivery timelines, team allocation, risk management and task prioritisation
• Mentor engineers, conduct performance reviews and provide actionable feedback to support professional growth
• Evaluate and enhance engineering processes, tools and methodologies to improve efficiency and productivity
• Partner with business stakeholders, product managers and designers to translate requirements into technical solutions
• Enforce technology standards, facilitate peer reviews and implement robust testing practices
• Manage and mitigate technology and model risks, strengthening controls and governance
• Advise senior stakeholders on technical strategy, alignment and cross-functional impact

Requirements

• 16-25 years of overall experience in software or AI/ML engineering, including significant leadership experience
• Strong understanding of LLMs, transformers, agentic frameworks, vector stores and search algorithms
• Strong Python proficiency with GenAI and agentic frameworks such as LangChain, LangGraph and CrewAI
• Hands-on experience with the AWS ML ecosystem (Bedrock, SageMaker, Lambda, API Gateway)
• Deep understanding of prompt engineering and prompt management, plus experience with SQL, NoSQL and vector databases (e.g., DynamoDB, PGVector, ChromaDB, FAISS)
• Experience with at least one major cloud platform (AWS, GCP or Azure) and large-scale AI/ML systems
• Experience in model risk management and guardrails development
• Bachelor's degree in Computer Science, Information Technology or Engineering

Skills

Large Language Models (LLMs), Transformers, Agentic frameworks, Python, LangChain, LangGraph, CrewAI, AWS ML ecosystem (Bedrock, SageMaker, Lambda, API Gateway), Prompt engineering, SQL/NoSQL and vector databases (DynamoDB, PGVector, ChromaDB, FAISS), REST APIs, JSON/XML, CI/CD tools (Jenkins), Cloud-native architectures, GCP or Azure, Model risk management, Guardrails development, Financial services experience, Team leadership and mentoring