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) supporting AI workloads.
• Experience with cost optimization for LLM API usage and compute budgeting.
• Background in change management or organizational AI transformation initiatives.
• Familiarity with basic Python/SQL for reading technical documentation