Manager - AI & Data

1. Role Summary

The Manager - AI & Data will lead the design and delivery of complex AI and GenAI solutions for clients across public and private sectors. The role is techno-functional, requiring strong hands-on capability in solution architecture, AI product design, and end-to-end delivery of AI initiatives-from problem framing through production deployment and value realization. This role is accountable for solution quality, technical design decisions, and delivery outcomes , and it is not just limited to advisory and oversight.

2. Key Responsibilities

• Enterprise Applications Management
• Security Groups Maintenance
• Subscription management
• Cloud and Networking Architecture design, implementation, management
• DevOps
• Fortify and SNYK launch
• BRD, FCD and TRD definition
• GTOM documentation update
• 10 developers daily tasks set up at code functions level
• Code QA and pull requests approval.
• React, python, fastapi, docker code issues remediation
• UAT design and perform

3. Required Experience & Skills

Technical & Functional Expertise

9 -14+ years of experience in data, analytics, or AI roles with direct delivery accountability

Strong understanding of:

• Machine learning fundamentals and applied AI
• Generative AI and LLM architectures
• Data engineering concepts supporting AI workloads
• Proven experience delivering production-grade AI solutions, not just prototypes and POCs

AI & GenAI Capabilities

Exposure to:

• LLM orchestration frameworks
• Prompt engineering and retrieval-augmented generation (RAG)
• Model evaluation, bias, and performance considerations
• Practical understanding of AI governance, model risk, and responsible AI considerations

Consulting & Leadership

Experience working in client-facing environments

Ability to balance technical depth with commercial and delivery constraints

Strong communication skills for technical and non-technical audiences

Cloud & Engineering (desirable)

Experience and exposure to at least one Hyperscaler

Ability to design scalable, secure AI architectures

9 -14+ years of experience in data, analytics, or AI roles with direct delivery accountability

Strong understanding of:

• Machine learning fundamentals and applied AI
• Generative AI and LLM architectures
• Data engineering concepts supporting AI workloads
• Proven experience delivering production-grade AI solutions, not just prototypes and POCs

Exposure to:

• LLM orchestration frameworks
• Prompt engineering and retrieval-augmented generation (RAG)
• Model evaluation, bias, and performance considerations
• Practical understanding of AI governance, model risk, and responsible AI considerations

Experience working in client-facing environments

Ability to balance technical depth with commercial and delivery constraints

Strong communication skills for technical and non-technical audiences

Experience and exposure to at least one Hyperscaler

Ability to design scalable, secure AI architectures