[Hiring] Technical Project Manager @TekCommands

Role Description

We are seeking an experienced Technical Project Manager to lead the end-to-end delivery of AI/ML and Generative AI initiatives. This role requires a hybrid skill set — strong technical fluency in AI/ML systems combined with proven program and delivery management expertise. The ideal candidate will drive projects from ideation through production deployment, working closely with data scientists, ML engineers, product owners, and business stakeholders to ensure on-time, on-budget, high-quality delivery.

Key Responsibilities

• Project Delivery & Execution
  • Lead end-to-end delivery of AI/ML and Generative AI projects — from ideation, discovery, and proof-of-concept through model development, testing, and production deployment. (Mandatory)
  • Develop comprehensive project plans, roadmaps, budgets, timelines, and resource plans.
  • Define and manage risk mitigation strategies, contingency plans, and issue escalation paths.
  • Manage project scope, cross-team dependencies, milestones, and deliverables to ensure successful execution.
  • Coordinate data availability, model training/validation cycles, MLOps pipelines, and infrastructure provisioning with technical teams.
• Agile Delivery & Process Leadership
  • Drive Agile, Scrum, or SAFe delivery practices across cross-functional teams (data science, engineering, product, QA).
  • Facilitate sprint planning, backlog grooming, stand-ups, retrospectives, and PI planning as applicable.
  • Establish and enforce delivery governance, documentation standards, and quality gates specific to AI/ML workflows (e.g., model validation, bias/fairness checks, responsible AI reviews).
• Stakeholder & Executive Communication
  • Track and communicate project status, risks, dependencies, and business outcomes to stakeholders, sponsors, and leadership.
  • Translate technical AI/ML concepts into business-relevant insights for non-technical stakeholders.
  • Prepare and present steering committee updates, dashboards, and executive-level reporting (e.g., KPIs, ROI, model performance metrics tied to business value).
• Cross-Functional Coordination
  • Partner with Data Science, ML Engineering, Product, Legal/Compliance, and Infrastructure teams to align priorities and resolve blockers.
  • Manage vendor and third-party tool/platform relationships where applicable (e.g., cloud AI services, LLM providers).
  • Ensure alignment between AI/ML roadmaps and broader organizational technology and business strategy.
• Risk, Compliance & Governance
  • Identify and manage risks specific to AI/ML projects — data privacy, model drift, hallucination/accuracy issues (for GenAI), security, and ethical AI considerations.
  • Ensure projects adhere to relevant regulatory, compliance, and responsible AI governance frameworks.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field (Master's preferred).
• [X]+ years of experience in technical project/program management, with demonstrated delivery of AI/ML or Generative AI initiatives.
• Strong understanding of the AI/ML lifecycle (data collection, feature engineering, model training, validation, deployment, monitoring) and GenAI concepts (LLMs, prompt engineering, RAG, fine-tuning).
• Proven experience managing Agile/Scrum/SAFe delivery frameworks.
• Experience managing budgets, resource allocation, and multi-team dependencies.
• Excellent stakeholder management and executive communication skills.
• PMP, CSM, SAFe Agilist, or equivalent certification preferred.

Preferred Qualifications

• Hands-on familiarity with ML/AI tools and platforms (e.g., Python, Jupyter, MLflow, SageMaker, Vertex AI, Azure ML, Databricks).
• Exposure to LLM ecosystems and GenAI tooling (OpenAI, Anthropic, LangChain, vector databases).
• Experience with MLOps practices and CI/CD pipelines for ML models.
• Background in a technical role (engineering, data science) prior to moving into project/program management.
• Experience working in regulated industries (finance, healthcare) with AI governance requirements.

Key Skills

• Project Management: Scope/risk/budget management, roadmapping, resource planning
• Delivery Methodology: Agile, Scrum, SAFe, Kanban
• Technical Fluency: AI/ML lifecycle, GenAI/LLM concepts, MLOps, cloud platforms
• Communication: Executive reporting, stakeholder management, technical translation
• Tools: Jira, Confluence, MS Project, Smartsheet, ML platforms (as applicable)