Key Responsibilities

- Lead and manage AI/ML/GenAI engineering teams responsible for developing enterprise AI solutions.

- Provide hands-on engineering leadership across architecture, design, development, testing, deployment and production support.

- Manage engineers, technical leads and cross-functional technical teams.

- Drive the complete engineering lifecycle from requirements design development testing deployment production.

- Establish and drive Agile/Scrum practices including sprint planning, backlog refinement, stand-ups, reviews and retrospectives.

- Work closely with Product Managers, Data Scientists, AI/ML Engineers, Architects and business stakeholders.

- Review technical designs, solution approaches and engineering decisions.

- Identify and resolve technical risks, dependencies, resource constraints and engineering bottlenecks.

- Ensure engineering teams follow best practices around coding, testing, CI/CD, DevOps, security, scalability and maintainability.

- Mentor engineers and technical leads and build high-performing engineering teams.

- Participate in hiring, performance management, career development and capability building.

- Drive technical roadmap and engineering strategy for AI initiatives.

- Lead development and implementation of AI/ML, GenAI, LLM, RAG and Agentic AI solutions.

- Ensure AI solutions are production-ready, scalable, reliable and cost-efficient.

- Collaborate with global and senior stakeholders and communicate technical progress, risks and outcomes.

- Drive continuous improvement in engineering processes,



productivity and quality.

Required Skills & Experience

- 10+ years of overall IT experience with significant experience in Engineering Management.

- Proven experience managing software/AI/ML engineering teams.

- Strong technical/engineering background, preferably starting as a Software Engineer, AI Engineer, ML Engineer, Data Engineer, Data Scientist or similar technical role.

- Hands-on experience with AI/ML/Generative AI projects.

- Strong understanding of AI/ML engineering lifecycle and production implementation.

- Experience with GenAI, LLMs, RAG, AI Agents or related technologies.

- Strong experience in Agile/Scrum methodologies.

- Experience managing sprint execution, engineering backlogs, priorities and technical dependencies.

- Solid understanding of SDLC, software architecture, APIs, cloud, CI/CD and DevOps.

- Experience with engineering team management, mentoring, hiring and performance management.

- Ability to review and challenge technical designs and guide engineering teams on technical decisions.

- Strong communication, stakeholder management and problem-solving skills.

Good to Have

- Experience with AWS / Azure / GCP.

- Python or other programming experience.

- Databricks / Snowflake / modern data platforms.

- MLOps / LLMOps.

- Azure OpenAI / OpenAI APIs.

- LangChain / LangGraph.

- Vector databases and RAG architectures.

- Agentic AI / multi-agent systems.

- Experience building enterprise-scale AI platforms.

- PMP / Scrum / Agile / Cloud / AI certifications.

📌 Engineering Manager - AI (Bengaluru)
🏢 Vaisesika Consulting
📍 Bengaluru