Product Manager

TEKsystems

. Own the product vision, roadmap, and backlog for enterprise data and agentic AI capabilities .

Posted 10/10/2026full-timeRemote • Oregon • United StatesSeniorLead💰 $128,000 - $192,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in product management for enterprise DataOps and AI capabilities, with a strong focus on translating business needs into actionable product requirements and ensuring data quality and operational efficiency. Proven ability to lead cross-functional teams and manage complex project delivery in compliance-heavy environments.

Highest-signal resume keywords

Product ManagementDataOps PlatformsAI/ML SystemsStakeholder ManagementAgile Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingData QualityMetadata ManagementAgent OrchestrationRAG PipelinesOpen APIsProgram PlanningAcceptance Criteria DevelopmentSuccess Metrics DefinitionWorkflow Graphs

Soft Skills

Strong CommunicationStakeholder ManagementIndependent Problem Solving

Tools & Technologies

MLOpsDataOpsLLMOpsAI ToolsVector Databases

Certifications & Qualifications

Bachelor's Degree in Computer ScienceAdvanced Degree (Preferred)

Industry Keywords

Enterprise DataComplianceRegulated IndustriesClient-Facing DeliveryOperational Efficiency

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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