Tech Prod. Manager

Global Data Insight & Analytics organization is looking for a Technical Product Manager focused on building and driving the strategy forward for our internal Data Science / AI/ML platform. This role will work in a small cross-functional team. The position will collaborate directly and continuously with other engineers business partners product managers and designers and will release early and often. The team you will be working on is focused on building Mach1ML platform an AI/ML enablement platform to democratize Machine Learning across Ford enterprise

We are seeking a dynamic and deeply technical leader for a unique dual role that combines strategic product management with hands-on technical expertise. As aSenior Technical Product Manager you will not only define the vision and roadmap for our cutting-edge Generative AI and Machine Learning Platform but also serve as a subject matter expert and hands-on contributor in a core engineering discipline.

You will collaborate with Product Owners Tech Anchors and world-class engineers to build the foundational tools pipelines and infrastructure that empower data scientists and developers across the enterprise. This role is for the product leader who loves to stay close to the code architect solutions and solve complex engineering challenges in the AI/ML space.

What Youll Do (Core Technical Product Management Responsibilities):

Product Vision & Strategy:Partner with the Product Owner to translate the high-level vision road mapping for our GenAI products or platform into a clear actionable strategy and a prioritized backlog of user stories Define and manage the product roadmap focusing on delivering tangible value through iterative development and deliberate prioritization. Leverage latest of Google Cloud services and Kubernetes technologies. Grow technical capabilities / expertise and provide guidance to other members on the team.

Stakeholder Collaboration & Technical Influencer:Act as the primary technical liaison between the development team and stakeholders translating business needs into technical requirements and vice-versa. Champion and help standardize best practices for MLOps and Generative AI development including RAG (Retrieval-Augmented Generation) fine-tuning and agentic workflows. Experiment with emerging technologies and share your knowledge to elevate the entire team. Lead by example in use of Paired Programming for cross training/upskilling problem solving and speed to delivery.

Agile Leadership & Delivery:Facilitate Agile ceremonies (sprint planning stand-ups retrospectives) and lead technical working sessions to unblock the team and drive progress. Work with software and ML engineers to tackle challenging MLOps problems. Work with the team to help build tools/ML Pipeline and systems using Python that make data scientists happier and more productive. Focus on delivering product value through careful and deliberate prioritization. Facilitate Agile ceremonies with the product team and working sessions with the stakeholder group(s). Help innovate standardize machine learning development practices. Experiment innovate and share knowledge with the team.

Specialization (Your Area of Deep Expertise):

In addition to your product duties you will be a hands-on expert and key contributor inoneof the following domains. You will dedicate a portion of your time to architecture coding and solving critical problems within your chosen specialty.

1. AI Ops / MLOps Expert:

• Design and implement CI/CD/CT pipelines for automated model training validation and deployment.
• Architect and manage scalable infrastructure on GCP and Kubernetes (GKE) for model serving and GPU workloads.
• Implement robust monitoring logging and alerting for model performance data drift and system health.

2. Software Engineering (Scale) Expert:

• Develop optimize and productionize complex ML and LLM-based applications.
• Implement advanced RAG pipelines including chunking strategies vectorization and integration with vector databases (e.g. Elastic PgVector).
• Architect and build high-throughput low-latency microservices and REST APIs to serve models and data.
• Own the design of resilient scalable backend systems capable of handling enterprise-level traffic.
• Champion elite coding practices including Test-Driven Development (TDD) paired programming and rigorous code reviews.

3. Data Engineering Expert:

• Design and build scalable data ingestion and processing pipelines using tools like Spark Kafka and Beam.
• Engineer data models and warehousing solutions optimized for large-scale analytics and ML training datasets.
• Ensure data quality governance and security across all data-centric platform components.

4. Solution Architecture Expert:

• Design end-to-end technical blueprints for complex AI/ML solutions on Google Cloud Platform (GCP).
• Evaluate and select the optimal combination of cloud services (e.g. Vertex AI BigQuery Cloud Functions GKE) to meet product requirements.
• Ensure solutions are secure scalable cost-effective and aligned with enterprise architecture standards.

5. Python Full Stack Expert:

• Develop both backend services (using FastAPI Flask) and frontend interfaces (using React NextJs or similar frameworks) for our AI platform and tools.
• Build intuitive UIs and interactive applications that make data scientists more productive and happier.
• Own the end-to-end development of internal applications from database to browser.

• A Bachelors or Masters degree in Computer Science Computer Engineering or a similar technical discipline.
• 5 years of combined experience in roles such as Technical Product Management Software Engineering or Solution Architecture within the AI/ML domain.
• Demonstrated deep hands-on expertise in at least one of the five specialization areas listed above.
• Proven experience leading product development within an Agile framework using tools like Jira.
• Strong hands-on proficiency withPythonand experience with modern software development practices (Git Docker Kubernetes) reusable API service development
• Deep understanding of the MLOps lifecycle and experience building or using enterprise-level ML platforms.
• Practical experience building applications with modern GenAI frameworks and libraries (Hugging Face LangChain/LangGraph LlamaIndex) and an understanding of the underlying concepts (e.g. embeddings vector stores agentic systems).
• 3 years of hands-on experience with cloud services preferablyGCP(especially Vertex AI GKE BigQuery Cloud Functions).
• Exceptional communication skills with the ability to lead teams articulate a technical vision and navigate complex decisions in a fast-paced environment.
• Ability to lead teams understand and rapidly learn technical acumen in AI/ML space gather requirements understand the customer come up with solutions.