Engineering Program Manager

Job Description

Roles & Responsibilities :
Managerial & Strategic

• Lead and mentor a multidisciplinary AI engineering team (ML engineers, data scientists, AI agents specialists, etc.).

• Translate business strategies into product/technology roadmaps and delivery plans.

• Work closely with Enterprise Architecture, Product, and Leadership to ensure strategic alignment and platform-scale feasibility.

• Manage project budgets, resources, timelines, and vendor relationships.

• Define OKRs, KPIs, and value outcomes for AI-driven initiatives.

• Ensure knowledge sharing, documentation, and operational playbooks for AI platforms and agentic solutions.

Technical & Delivery Execution

• Plan and oversee the development lifecycle of agentic AI systems, including data pipelines, LLM/agent orchestration, evaluation frameworks, and integration layers.

• Coordinate with the Enterprise Architect to ensure solution integrity, scalability, compliance, and interoperability with enterprise systems.

• Drive the execution of proof-of-concepts, prototypes, and pilot deployments, transitioning them to production environments.

• Facilitate architectural discussions related to:

  • LLM selection, fine-tuning, and observability

  • Agentic workflow frameworks and orchestration tools

  • API integrations, microservices, and system interoperability

  • Data security, access governance, and MLOps

• Oversee QA, testing, benchmarking, and performance evaluation of AI models and agent workflows.

Business & Stakeholder Management

• Act as the primary liaison among technical teams, business stakeholders, and external partners.

• Gather and prioritize requirements from business units and stakeholders.

• Convert business requirements into technical specifications, acceptance criteria, and success metrics.

• Present project progress, risk posture, and performance insights to executives.

• Drive change management, adoption strategies, training, and enablement for AI-enabled workflows.

Qualifications

Experience & Qualifications

• 5+ years of experience in technology program/project management, product delivery, or solution ownership roles.

• Experience working on AI/ML, data platforms, enterprise SaaS, or agentic/automation technologies.

• Background working with cross-functional engineering, architecture, and business teams in large, complex organizations.

• Demonstrated success delivering enterprise technology initiatives from inception through production deployment.

• Strong business acumen to connect AI investments with ROI, operational efficiency, or revenue impact.

Additional Information

Required Skills & Competencies

Business & Leadership

• Strong strategic thinking with ability to articulate business value of AI initiatives.

• Excellent stakeholder management, communication, and presentation skills.

• Proven ability to manage cross-functional teams in fast-evolving technical environments.

• Skilled in Agile methodologies (Scrum, Kanban) and modern delivery management practices.

Technical Knowledge (Manager-Level)

• Good understanding of:

  • Machine Learning and LLM concepts

  • AI agentic architectures and tool orchestration frameworks

  • Data pipeline architecture, storage, and governance

  • APIs, microservices, and cloud-native solution patterns

  • DevOps/MLOps fundamentals (CI/CD, model lifecycle management)

• Ability to evaluate technical tradeoffs and advise on solution approaches (without needing to build them directly).

Project Management

• Strong experience with planning, scheduling, sprint and backlog management, and risk mitigation.

• Experience integrating external vendors, platform partners, and third-party AI tools.