Senior AI Product Manager, Context Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the enterprise context layer that drives WEX's global fleet of AI agents.

• Collaborate with global product, engineering, and business leaders to prioritize and organize context initiatives.

• Manage the semantic object roadmap for fundamental enterprise entities, defining certified measures, join graphs, and Row-Level Security.

• Set standards for federated ingestion, chunking, caching, metadata, and citation enforcement.

• Integrate legacy knowledge APIs into cohesive, multi-tenant interfaces.

• Design and deliver production-ready context packs for essential operational workflows and Standard Operating Procedures (SOPs).

• Analyze retrieval traces, troubleshoot failures, and enhance context consumption alongside agent teams.

• Develop and maintain evaluation harnesses, golden datasets, error taxonomies, and quality gates.

• Incorporate auditability, data lineage, least-privilege access, and responsible AI safeguards into the context layer.

• Monitor return on investment through API cost reduction, task resolution improvements, and operational risk alleviation.

• Connect unstructured knowledge, governed semantic data, and agent execution workflows across global teams.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Engineering, Business, or a related field, or equivalent practical experience.

• Senior-level Product Management experience managing data platforms, enterprise search/retrieval systems, semantic layers, API products, or internal developer platforms utilized by engineering teams.

• Profound understanding of applied generative AI and agentic systems, including advanced RAG, embeddings, chunking, metadata management, grounding, and context window assembly.

• Significant experience with structured enterprise data, relational models, certified metrics, and natural-language querying over raw database schemas.

• Proficiency in inspecting retrieval traces, interpreting SQL query plans, reviewing JSON/YAML configurations, and executing API calls.

• Experience in designing and executing evaluation harnesses, golden benchmark datasets, error taxonomies, and quantitative quality gates.

• Familiarity with authentication/identity, tenant isolation, Row-Level Security (RLS), audit logging, and data privacy.

• Outstanding written and verbal communication skills in English.

• Ability to align and influence global engineering, security, compliance, and executive stakeholders without direct authority.

• Experience with Knowledge Graphs, ontologies, taxonomies, and enterprise entity resolution (MDM) is a plus.

• Knowledge of headless BI, metric stores, or governed NL-to-SQL products is a plus.

• Background in payments, fintech, benefits, healthcare-adjacent platforms, or other highly regulated sectors is a plus.

• Experience with vector databases, automated RAG evaluation frameworks, or agent tool protocols is a plus.

• Proven track record of consolidating or replacing legacy enterprise knowledge management or search systems in production is a plus.

🏝️ Benefits

• Health insurance

• Dental insurance

• Vision insurance

• Retirement savings plan

• Paid time off

• Health savings account

• Flexible spending accounts

• Life insurance

• Disability insurance

• Tuition reimbursement

• Quarterly or annual bonus eligibility for non-sales roles