Role: Sr Manager, AI Engineering

Experience: 12 16 Years

Location: Bengaluru (work from office)

CTC: 45 70 LPA (including 25% variable)

Position Summary

My client organization is hiring a Sr Manager, AI Engineering to lead a team that builds and deploys enterprise Generative AI (GenAI) and Agentic solutions and to own the stakeholder relationships behind their delivery. Spanning more than one business unit and function, this is a predominantly strategic leadership role (approximately 70% strategy and 30% hands-on execution). You will set the technical direction for GenAI at my client organization, translate business needs into architecture and solution designs, and guide a multidisciplinary team through end-to-end delivery.

You will solve ambiguous, enterprise-scale AI problems — selecting models and patterns across GenAI, resolving integration challenges, and closing architecture gaps, risks and dependencies — while partnering closely with business and technology leaders to build tools and capabilities that generate value across the enterprise.

Primary Responsibilities

- Lead, coach and develop a team of AI engineers delivering GenAI solutions; set engineering standards, priorities and delivery expectations, and manage performance and career growth.
- Own the AI engineering strategy and roadmap across more than one business unit and function, aligning delivery with enterprise objectives.
- Partner with Business and Product owners, AI Architects, Data Architects, Data Stewards, Data Engineers, ML Engineering, Full-Stack Developers and Enterprise Architecture to ensure end-to-end alignment.




- Translate business requirements into system architecture, solution flows and configuration specifications.
- Recommend architecture patterns, reusable components and model-selection strategies across GenAI (LLMs, RAG, agentic workflows, context engineering), balancing cost, latency, accuracy, reliability, security and privacy.
- Drive disciplined evaluation and error-analysis loops and Responsible AI practices to keep non-deterministic systems predictable and trustworthy.
- Identify architecture gaps, risks and dependencies early and propose mitigation strategies for ambiguous, enterprise-scale problems.
- Manage relationships with external platform partners (e.g., Microsoft Azure, Snowflake), model providers and third-party implementation partners.
- Represent AI engineering to senior and executive leaders (Directors, VPs); communicate progress, trade-offs and risks, and act as the decision maker on architecture, model selection and delivery within enterprise standards and guardrails.
- Build tools and capabilities that generate value across the enterprise, providing advisory and indirect impact to business outcomes.

Qualifications

- Master’s degree in computer science, Engineering,



Information Technology or a related field (or a Bachelor's degree with equivalent professional experience).
- 5–7 years of relevant experience in AI/ML, software or solution architecture, or technical leadership, including experience leading and/or mentoring engineers.
- Hands-on experience building and deploying GenAI solutions such as chatbots and agents on a major cloud platform, preferably Microsoft Azure.
- Proven ability to translate business requirements into technical design documents and system configurations.
- Working expertise with LLMs, RAG, prompt and context engineering, and agentic workflows, LangGraph, grounded in evals and error analysis.
- Strong software-engineering fundamentals and the judgment to make sound trade-offs across cost, scalability, reliability, security and privacy.
- Excellent stakeholder-management and communication skills, with the ability to influence and bridge technical and business audiences.

Domain Expertise

- Enterprise GenAI solution delivery across multiple business units or functions.
- Familiarity with the contemporary data and AI stack (e.g., Azure AI / OpenAI services, Snowflake) and integration across data, models and applications.
- Understanding of Responsible AI, security, privacy and governance in an enterprise setting.

Individual Skills

- People leader who builds diverse teams and sets a high bar for engineering quality and delivery.
- Strong problem solver, comfortable with ambiguity and enterprise-scale complexity.
- Confident communicator and influencer with senior and executive stakeholders.

📌 Sr Manager AI Engineering (Bengaluru)
🏢 ConsultMeIn
📍 Bengaluru