Role Title : Senior Gen AI Engineering Manager
Position Summary :
Leads a team of Generative AI engineers, GenAIOps Engineers and Data Scientists in the hands-on design, development, deployment, and operationalization of advanced Generative AI solutions. Translates strategic AI objectives into actionable, high-impact initiatives that drive business value. Ensures the design, architecture, and implementation of scalable GenAI applications using leading LLMs (e.g., OpenAI, Gemini, Llama) and multi-modal models within Azure and other cloud platforms, while fostering a culture of innovation, technical excellence, and ethical AI practices. This position emphasizes technical leadership, solution delivery, and team management. Oversees end-to-end project execution, ensures robust and production-ready AI systems, and mentors team members to build technical depth. By aligning with enterprise architecture and collaborating with cross functional stakeholders, this role drives the adoption of cutting-edge GenAI technologies and supports the broader goals of the Innovation Analytics & AI team.
Job Responsibilities :
- Technical Leadership & Solution Delivery : Leads the strategy, design, and implementation of scalable Generative AI solutions using LLMs (e.g., OpenAI, Gemini, Llama2, GPT-4), multi-modal models, and tools like Promptflow, Azure AI Search, LangChain, Semantic Kernel, and Vector DBs. Oversees the development of robust data pipelines and Retrieval Augmented Generation (RAG) workflows, ensuring performance, scalability, and ethical compliance through rigorous testing (ground truth, contextual accuracy, semantic similarity, bias detection, hallucination analysis, benchmarking). Reviews technical designs and architectures for alignment with business needs and enterprise standards, ensuring production-ready deployments using Kubernetes, Terraform, and CI / CD pipelines.
- Team Management & Development : Manages a team of GenAI engineers and data scientists, providing mentorship, performance evaluations, and career development guidance. Fosters a collaborative, innovative, and inclusive team culture focused on continuous learning and technical excellence. Supports onboarding, sets clear objectives, and builds team capabilities in GenAI tools, prompt engineering, and model optimization. Encourages experimentation with emerging technologies to drive innovation.
- Project Execution & Stakeholder Collaboration : Translates strategic AI priorities into actionable project plans with clear milestones, timelines, and deliverables. Collaborates with Solution Architects, product owners, and business stakeholders to ensure alignment, transparency, and impact of GenAI solutions. Provides regular updates on project progress, risks, and outcomes to senior management. Ensures seamless integration of GenAI solutions with enterprise architecture and data platforms.
- Innovation & Technical Expertise : Evaluates emerging GenAI technologies, frameworks, and methodologies to enhance organizational AI capabilities. Contributes to the development of reusable GenAI assets, model catalogs, and standards to improve solution delivery. Acts as a subject matter expert in GenAI, leading internal learning forums and promoting the adoption of innovative tools and practices. Stays current with industry trends to maintain a competitive edge.
Skill and Experience :
9-15 years of experience required to perform essential job functions.Additional Experience Qualifier (optional) : 10+ years preferred, with demonstrated expertise in designing, architecting, and deploying Machine Learning / AI and GenAI solutions in production environments. Experience leading technical teams in GenAI, RAG workflows, and cloud-native AI architectures is preferred.Advanced proficiency in Python, .NET, or C# for AI application development. Expert-level knowledge of GenAI tools (Promptflow, Azure AI Search, Semantic Search, Hybrid Search, Document Intelligence, Skillsets, Generative RAG Search, Vector DBs, Azure OAI, AI Hub, Agents, Assistants, LangChain, Hugging Face, Llama Index, Semantic Kernel)Deep expertise in leading LLMs (OpenAI, Gemini, Llama2, GPT-4) and multi-modal models Strong understanding of cloud-native architectures, Kubernetes, Terraform, and API development Proficiency in MLOps practices, including CI / CD pipelines, automated testing, and model monitoringAdvanced knowledge of ethical AI practices (bias detection, hallucination analysis, performance benchmarking)Proven ability to lead end-to-end development and deployment of GenAI solutionsExceptional leadership, mentorship, and strategic communication skills for cross-functional collaborationAbility to translate business problems into scalable, production-ready AI solutions Commitment to driving innovation and aligning AI strategies with enterprise goalsMust Have Skills :
Required : AI Platforms, Azure, Databricks, Python, Software Engineering (enterprise applications), SQL, Generative AISoft skills : Communication, project management, coaching / mentoring, leadershipEducation and Certifications :
B.E / B.Tech in EngineeringWork location : Bengaluru