Product Manager

Job Description:

• Own the product vision, roadmap, and backlog for enterprise data and agentic AI capabilities
• Translate business needs into outcome-driven product/service requirements and architecture
• Define success metrics for data reliability, AI agent effectiveness, automation value, and operational efficiency
• Develop PRDs, user stories, and acceptance criteria focused on operability, reuse, and scalability
• Lead cross-functional delivery across data engineering, ML engineering, platform, security, and client stakeholders
• Plan and execute programs spanning DataOps, MLOps, and Agentic AI workflows using Agile methods and AI tools
• Manage dependencies, risks, timelines, and multiple client workstreams
• Establish delivery governance, design reviews, readiness checks, operational handoffs, and post-launch validation
• Drive implementation and modernization of enterprise DataOps capabilities, including ingestion, transformation, orchestration, data modeling, metadata, lineage, data quality, and observability
• Partner with architects to ensure data tooling is production-ready, secure, and governed
• Define and track data SLAs, quality thresholds, and operational metrics
• Lead productization and delivery of Agentic AI systems, including agent orchestration, RAG, tool-using agents, and multi-agent workflows
• Ensure prompt/workflow versioning, evaluation frameworks, benchmark testing, human-in-the-loop controls, fallbacks, observability, logging, and traceability
• Balance accuracy, latency, cost, reliability, and safety through experimentation and data-driven tuning
• Partner with security, legal, and compliance teams on PII handling, model access, prompt retention, auditability, change management, and incident response
• Serve as a trusted partner to client product delivery leaders and sales executives
• Communicate tradeoffs, progress, risks, and value realization across client and internal ecosystems

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data/Analytics, or equivalent experience
• 7–10 years of experience across Product Management and/or Product Operations
• Proven experience delivering enterprise DataOps platforms, quality data sets, and/or AI/ML systems into production
• Practical experience with RAG pipelines, embeddings, vector databases, agent orchestration, workflow graphs, and tool/function calling using open APIs
• Experience authoring PRDs, roadmaps, program plans, and executive readouts
• Strong communication and stakeholder-management skills in enterprise environments
• Background in consulting or client-facing delivery environments such as Sales Support
• Ability to operate independently on ambiguous and complex problem spaces
• Ability to make architectural and product tradeoffs grounded in data and delivery realities
• Advanced degree is a plus
• Experience delivering AI solutions in regulated or compliance-heavy industries is preferred
• Familiarity with LLM hosting and deployment patterns
• Exposure to LLMOps and MLOps using open tooling
• Experience designing reference architectures or accelerators for reuse across clients
• Hands-on understanding of orchestration, transformation/modeling, data quality/validation, and metadata/lineage tooling

Benefits:

• Medical, Dental, and Vision
• Critical Illness, Accident, and Hospital coverage
• 401(k) Retirement Plan with pre-tax and Roth post-tax contributions
• Life Insurance (Voluntary Life and AD&D for employee and dependents)
• Short and Long-Term Disability
• Health Spending Account (HSA)
• Transportation Benefits
• Employee Assistance Program
• Time Off/Leave (PTO, Vacation or Sick Leave)
• Additional earnings may be available through annual bonuses and profit sharing