Project Management Manager - (Genai)

Job Description: Project Manager – Generative AI (GenAI) About the Role We are seeking an experienced Project Manager with Generative AI (GenAI) expertise to lead the planning, execution, and delivery of AI-driven initiatives across the organization. This role sits at the intersection of traditional program management and emerging AI technology delivery — you'll coordinate cross-functional teams (data science, ML engineering, product, legal/compliance, and business stakeholders) to ship LLM-powered products, copilots, RAG pipelines, and agentic workflows on time, within budget, and aligned with responsible-AI standards. This is a high-visibility role for someone who can speak fluently to both engineering teams building on foundation models and executives evaluating GenAI ROI. Key Responsibilities 1. Program & Delivery Management Own end-to-end project lifecycle for GenAI initiatives: discovery, scoping, resourcing, execution, UAT, deployment, and post-launch monitoring. Build and maintain integrated project plans, roadmaps, RAID logs, and dependency maps across multiple concurrent AI workstreams. Define and track KPIs/OKRs for model performance, adoption, latency, cost-per-token, and business impact. Manage vendor and API relationships (OpenAI, Anthropic, Google, Azure OpenAI, AWS Bedrock, etc.), including contract SLAs and usage/cost governance. 2. GenAI-Specific Technical Coordination Translate business requirements into technical specifications for LLM fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation) architectures, and agentic workflows. Coordinate data pipeline readiness (labeling, embeddings, vector databases) with data engineering teams. Partner with ML/AI engineers on model evaluation frameworks (accuracy, hallucination rate, bias testing, red-teaming). Manage iterative experimentation cycles (A/B testing, prompt versioning, model comparison) typical of AI product development, as opposed to traditional linear SDLC. 3. Stakeholder & Risk Management Serve as primary liaison between technical AI teams and business/product stakeholders, translating complex AI concepts into clear business language. Identify and mitigate AI-specific risks: data privacy, model drift, hallucination/accuracy issues, IP/copyright exposure, and regulatory compliance (GDPR, EU AI Act, SOC 2, etc.). Drive responsible AI governance: documentation of model cards, audit trails, human-in-the-loop checkpoints, and ethical review processes. Manage change management and organizational readiness for AI adoption, including training and communication plans. 4. Agile & Cross-Functional Leadership Run Agile/Scrum or hybrid ceremonies (sprint planning, standups, retros) tailored to the iterative, experimental nature of AI development. Facilitate collaboration across data science, MLOps, product management, UX, legal, security, and executive sponsors. Manage budget forecasting and resource allocation across compute costs (GPU/token spend), tooling licenses, and headcount. Report program status, risks, and outcomes to senior leadership and steering committees. Required Qualifications Bachelor's degree in Computer Science, Engineering, Business, or related field (Master's/MBA preferred). 6–10+ years of project/program management experience, including 3+ years managing AI/ML, data science, or software product initiatives . Hands-on working knowledge of Generative AI concepts : LLMs, prompt engineering, RAG, fine-tuning, embeddings, vector databases (e.g., Pinecone, Weaviate, ChromaDB), and agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen). Familiarity with major LLM providers and platforms (OpenAI GPT, Anthropic Claude, Google Gemini, Azure OpenAI Service, AWS Bedrock). Strong command of project management methodologies (Agile, Scrum, Kanban, SAFe) and tools (Jira, Asana, MS Project, Monday.com). PMP, PMI-ACP, CSM, or SAFe certification (preferred). Demonstrated experience managing cross-functional teams of 10+ members across technical and non-technical disciplines. Excellent stakeholder management, executive communication, and presentation skills. Working knowledge of data privacy, security, and AI governance frameworks (GDPR, EU AI Act, NIST AI RMF). Preferred Qualifications Prior experience as a Technical Program Manager (TPM) or Product Manager in an AI/ML organization. Exposure to MLOps/LLMOps practices (model deployment pipelines, monitoring, versioning). Understanding of cloud infrastructure (AWS, Azure, GCP) supporti…