Engineering Manager _Generative AI

Role Overview: We are looking for an Engineering Manager Generative AI to lead the adoption of Large

Language Models (LLMs) and agentic AI solutions across enterprise business functions.

The role will focus on process automation, efficiency, simplification, risk reduction, and development of

scalable AI/ML solutions while providing technical leadership to engineering teams.

Key Responsibilities

• Lead and manage engineering teams delivering Generative AI and enterprise AI solutions.
• Drive adoption of LLMs, agentic workflows, and AI automation across business processes.
• Provide technical guidance on architecture, development, testing, and deployment.
• Mentor engineers and support their technical and professional development.
• Collaborate with product managers, business teams, designers, and senior stakeholders to translate

requirements into scalable technical solutions.

• Manage project timelines, resources, risks, priorities, and delivery.
• Establish engineering standards, code review practices, testing processes, and CI/CD workflows.
• Identify opportunities to improve engineering processes, productivity, and technology adoption.
• Ensure appropriate risk management, governance, security, and controls across AI solutions.

Technical Requirements

• 8–12 years of overall software/engineering experience, with significant experience in AI/ML or

Generative AI.

• Strong understanding of LLMs, Transformers, agentic frameworks, vector stores, and search

algorithms.

• Strong hands-on Python development experience.
• Experience with GenAI and agentic frameworks such as LangChain, LangGraph, CrewAI, or similar.
• Experience with AWS ML services, particularly Bedrock, SageMaker, Lambda, and API Gateway.
• Experience designing and developing high-performance, large-scale AI/ML systems.
• Strong knowledge of prompt engineering and prompt management.
• Experience with SQL, NoSQL, and vector databases, such as DynamoDB, PGVector, ChromaDB, or

FAISS.

• Experience with at least one major cloud platform: AWS, GCP, or Azure.
• Knowledge of AI model risk management and guardrail development.
• Good understanding of REST APIs, JSON/XML, CI/CD, Jenkins, and cloud-native architectures.

Leadership & Stakeholder Skills

• Proven experience leading and mentoring technical engineering teams.
• Strong communication, stakeholder management, and influencing skills.
• Ability to work with senior business and technology stakeholders.
• Strong problem-solving and strategic thinking abilities.
• Ability to balance technical priorities with business objectives.
• Experience working in a fast-paced, enterprise technology environment.

Preferred Experience

• Experience in financial services, banking, or other highly regulated industries.
• Experience delivering enterprise-scale Generative AI or ML platforms.
• Knowledge of technology risk, governance, controls, and compliance.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline