Engineering Manager (Generative AI)

Job Description

About the Role: We are looking for an experienced Engineering Manager (Generative AI) to lead client-facing AI/ML initiatives in a dynamic services environment. In this role, you will be the bridge between clients, data science teams, and engineering groups, ensuring the successful delivery of cutting-edge Generative AI solutions aligned to business goals. You will manage multiple concurrent projects involving emerging technologies like large language models (LLMs), diffusion models, and prompt engineeringwhile handling client communications, technical planning, and delivery governance. Key Responsibilities: Own and drive end-to-end Generative AI project delivery for clientsfrom pre-sales support and requirements gathering to deployment and post-launch support. Coordinate with cross-functional teams (data scientists, MLOps engineers, software developers, UI/UX designers) to translate client needs into scalable AI solutions. Manage project scope, timelines, budgets, and resource allocation across multiple client engagements. Conduct client workshops, create solution roadmaps, and define MVPs with measurable KPIs. Track progress using Agile methodologies and ensure timely delivery within SLA and quality standards. Guide internal teams on technology choices and delivery best practices in the Generative AI ecosystem (e.g., OpenAI, Hugging Face, LangChain, Pinecone, etc.). Support proposal development, solution architecture reviews, and pricing during pre-sales activities. Maintain clear, consistent communication with clients and internal leadership; manage escalations, risks, and delivery blockers proactively. Stay current with advancements in Generative AI and bring innovation to client engagements. Required Qualifications: 13+ years of experience in software development, GenAI, machine learning with at least 5 years in technical project management roles. Solid understanding of AI/ML workflows and hands-on familiarity with Generative AI concepts (LLMs, embeddings, vector search, prompt engineering, etc.). Conversant with Python and SQL. Practical experience in designing business solutions in these areas, and explaining those to the customers as part of pre-sales and/or delivery stage. Excellent analysis, and problem-solving skills. Deep thinking ability. Proven knowledge of data structure and algorithms. Proven track record of strong leadership and decision-making skills to drive consensus on requirements and ensure timely delivery of critical customer-facing AI features. Strong track record of developing, leading, coaching, and mentoring machine learning engineers and scientists is vital. Proficiency in Agile project management frameworks and tools (e.g., Jira, Confluence, Azure DevOps). Strong communication and stakeholder management skillsespecially in client-facing roles. Cultivate a positive and growth-oriented environment. Bachelors degree in a related field, such as computer science, software engineering or data science, is recommended; Master’s or MBA is a plus. Preferred Skills: Experience working with cloud-native AI stacks (AWS SageMaker, Azure ML, Google Vertex AI, etc.). Exposure to ML Ops and AI model lifecycle management. Technical certifications in AI/ML, cloud, or project management (e.g., PMP, PMI-ACP, CSM). Experience in consulting or delivering multi-region/global enterprise AI projects. What’s in it for You: Work with a fast-growing team on cutting-edge AI solutions across global clients. Opportunity to shape and scale next-gen AI delivery practices. Competitive compensation and flexible work arrangements. Access to continuous learning, certifications, and professional growth in the AI domain.