Technical Product Manager AI Infrastructure Data Platform

Benefits:

ONSITE

Competitive salary

Opportunity for advancement

Technical Product Manager, AI Infrastructure & Data Platform Dallas, TX ( Onsite ) In-Person Interview

About the Role We are looking for a Technical Product Manager, AI Infrastructure & Data Platform to lead the vision, strategy, and execution of our enterprise-scale AI infrastructure and data ecosystem. This role blends deep technical expertise in AI/ML systems with strategic product leadership, ensuring the design and delivery of scalable, secure, and efficient data and AI platforms that power our next-generation agentic and generative AI capabilities. You will collaborate with engineering, data science, and architecture teams to deliver reliable and high-performance foundations for AI products across the organization — spanning model orchestration, multi-agent coordination, data pipelines, and ML lifecycle management. This position is ideal for a seasoned product leader passionate about building enterprise-grade AI infrastructure, driving platform adoption, and enabling data-driven innovation at scale.

Key Responsibilities

Platform Vision & Strategy:

Define and execute the product vision and roadmap for the AI Infrastructure & Data Platform, aligning with enterprise AI and digital transformation strategies.

Lead the evolution of the underlying data fabric, MLOps, and agentic infrastructure enabling large-scale AI model training, deployment, and automation.

Partner with engineering and architecture teams to establish standardized agent frameworks, API ecosystems, and developer-facing tools.

Evaluate emerging technologies (e.g., AWS Bedrock, SageMaker, LangChain, LangGraph) and integrate them into the platform strategy.

Product Delivery & Execution

Translate business and technical requirements into actionable epics, features, and prioritized backlogs.

Partner with program management on PI Planning, dependency mapping, and milestone definition for each release cycle.

Drive the development and adoption of reusable data pipelines, orchestration layers, and service APIs that power enterprise AI applications.

Collaborate with Change Management to ensure readiness for platform releases, documentation, and stakeholder training.

Data & ML Platform Enablement

Define and manage the data platform strategy, including ingestion, governance, lineage, cataloging, and real-time data access.

Enable consistent, high-quality, and auditable data pipelines for AI and ML workloads.

Partner with AIOps/AgentOps to build systems for agent evaluation, observability, and performance monitoring.

Collaborate with Security, Compliance, and Legal to uphold enterprise AI governance standards and responsible AI practices.

Stakeholder & Customer Engagement

Collaborate with enterprise teams, data scientists, and engineers to identify pain points, gather feedback, and validate product-market fit.

Communicate product vision and technical trade-offs effectively to executive, business, and technical audiences.

Ensure customer satisfaction and drive continuous platform adoption through proactive engagement and measurable impact.

Qualifications Education

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.

Experience

8+ years of product management experience, with at least 3 years focused on AI/ML platforms, data infrastructure, or cloud systems.

Proven track record of delivering scalable platform products in complex enterprise environments.

Deep experience with cloud platforms (AWS, Azure, GCP), data pipeline tools, and modern MLOps ecosystems.

Familiarity with agentic AI frameworks, LLM architectures, RAG pipelines, and autonomous systems.

Technical Skills

Strong understanding of distributed systems, APIs, microservices, and data integration architectures.

Hands-on experience or working knowledge of:

AWS Bedrock, SageMaker, Lambda, ECS, EMR

LangChain, LangGraph, or similar agentic frameworks

Airflow, Databricks, Kafka, Spark, and Delta Lake

Monitoring and observability tools (Prometheus, Grafana, MLflow)

Knowledge of data governance, lineage tracking, and responsible AI frameworks.

Soft Skills

Exceptional communication, collaboration, and stakeholder-management skills.

Strong analytical and strategic thinking; able to balance short-term delivery with long-term platform evolution.

Adept at translating complex technical concepts into clear business value propositions.

Passionate about building developer-centric, scalable, and ethical AI systems.

Why Join Us

Be part of a high-impact Agentic AI initiative driving innovation across industries.

Work with cutting-edge AI and data technologies in a collaborative, forward-thinking environment.

Shape the foundation for enterprise-wide AI enablement and intelligence automation.