Gen AI Program Manager

Area(s) of responsibility

Technical Program Manager – AI, Automation & Data Science

Role Overview:

This is highly experienced Technical Program Manager role to lead a cutting-edge AI-driven product development initiative for a strategic customer. This role demands a deep understanding of AI, automation, data science, and machine learning, combined with strong product development program management expertise. The successful candidate will oversee cross-functional engineering teams, drive end-to-end execution, and align technical roadmaps with business goals while ensuring high-impact delivery in a dynamic, fast-paced AI ecosystem.

This is a high-impact leadership role for someone passionate about AI, automation, and enterprise-scale AI adoption. If you thrive in AI-first product environments and love solving complex problems with intelligent automation, this role is for you

Key Responsibilities:

1. Program Strategy & Roadmap Execution:

Define and execute the end-to-end program roadmap for AI-driven product development, ensuring alignment with customer goals and business impact.
Collaborate with AI scientists, ML engineers, data engineers, and software architects to drive feature development and continuous improvements.
Establish scalable program frameworks to manage milestones, risk assessment, and stakeholder expectations.
Foster an agile, iterative development approach to accelerate AI and GenAI adoption.
2. AI & Automation Product Development Leadership:
Guide the team in leveraging LLMs, AutoGen, agentic AI frameworks, and cutting-edge AI tools to build intelligent, automated solutions.
Oversee the full AI model lifecycle, including data acquisition, training, fine-tuning, deployment, and performance monitoring.
Ensure seamless integration of AI-driven automation across cloud, hybrid, and multi-cloud environments.
Partner with engineering to define scalability, reliability, and security best practices for AI-based platforms.
3. Cross-Functional Team Coordination & Execution:
Drive collaboration across data science, machine learning, DevOps, and platform engineering teams to ensure synchronized execution.
Facilitate effective communication between engineering, product, and business stakeholders.
Implement best practices for AI product lifecycle management, MLOps, and CI/CD pipelines.
Develop clear technical documentation and ensure knowledge-sharing among teams.

Essential job tasks

Required Skills & Experience:

Technical Expertise:

10+ years of experience in technical program management, with at least 5 years in AI, data science, or machine learning-driven product development.
Deep understanding of LLMs, Generative AI, AutoGen, CrewAI, WrenAI, and agent-based AI frameworks.
Strong knowledge of MLOps, AI/ML pipeline orchestration, and cloud-based AI architectures (Azure, AWS, GCP).
Hands-on experience with AI model deployment, fine-tuning, and AI-powered automation tools.
Expertise in Process Automation, RPA, and AI-driven process mining techniques.
Knowledge of vector databases, AI search technologies, and intelligent data processing frameworks.
Familiarity with Python, TensorFlow, PyTorch, LangChain, AutoML, and AI search indexing.
Program Management & Leadership:

Proven track record of managing AI-driven product development initiatives in highly technical environments.
Strong background in agile methodologies, sprint planning, and iterative development models.
Ability to drive cross-functional collaboration between AI research, data engineering, and platform teams.
Exceptional stakeholder management skills with the ability to communicate technical concepts to non-technical executives.
Deep experience in scaling AI solutions across enterprise ecosystems.
Soft Skills & Mindset:

Visionary leadership with a passion for emerging AI trends, automation, and digital transformation.
Strong problem-solving skills with the ability to drive high-impact AI solutions.
Excellent communication skills, capable of influencing engineering teams, data scientists, and business leaders.
Ability to navigate ambiguity and drive AI innovation in a fast-paced environment.
Must haves:

Experience in program managing building AI-powered enterprise platforms and automation systems.
Knowledge of Responsible AI principles, model interpretability, and AI governance frameworks.
Strong business acumen with the ability to bridge AI innovation with tangible business outcomes.
DevSecOps and AGILE Expertise with product management environments