Benefits:
- ONSITE
- Competitive salary
- Opportunity for advancement
Technical Product Manager, AI Infrastructure & Data Platform
Work Type: Full-Time, Onsite
Location: Dallas, Texas
Interview Mode: In-Person
Work Auth : Must be authorized to work in the U.S.
Domain: Enterprise AI / Agentic AI / AWS BedrockAbout the RoleWe 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.
QualificationsEducation- 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.