Senior AI Product Manager (Context Engineering)

WEX; Oregon; Hybrid; USD 125,000 - 154,000; Full time

Job summary

WEX is seeking a Senior AI Product Manager (Context Engineering) to own the enterprise context layer powering its global AI agents. In a hands-on builder role within the Data, AI, Risk & Product organization, you will bridge unstructured knowledge, governed semantic data, and agent workflows to ensure actions are grounded, authorized, and accurate.

You will partner with global engineering, data, and business teams to prioritize high-value context initiatives, design production-ready context

Qualifications

• Bachelor's degree in CS, Engineering, Business, or related field or equivalent experience.
• Senior-level PM experience owning data platforms, enterprise search/retrieval systems, semantic layers, API products, or internal developer platforms.
• Deep understanding of applied generative AI and agentic systems, incl. advanced RAG, embeddings, chunking, metadata management, grounding, and context window assembly.
• Strong experience with structured enterprise data, relational models, certified metrics, and NL querying over raw schemas.
• Hands-on depth: inspecting retrieval traces, reading SQL plans, reviewing JSON/YAML configurations, executing API calls.
• Experience designing and running evaluation harnesses, golden benchmark datasets, error taxonomies, and quality gates.
• Security & governance knowledge: authentication/identity, tenant isolation, Row-Level Security, audit logging, data privacy.
• Excellent written and verbal English communication to align with global stakeholders.

Responsibilities

• Partner with global product/engineering/business leaders to prioritize high-value context initiatives.
• Define semantic object roadmaps for accounts, claims, plans with RLS and certified metrics.
• Establish federated ingestion, chunking, caching, and metadata standards for enterprise knowledge.
• Design and deliver context packs for critical workflows; inspect retrieval traces and debug failures.
• Build evaluation harnesses, golden datasets, error taxonomies, and quality gates for retrieval and containment.
• Embed governance and ROI tracking for cost reduction and risk mitigation.

Skills

AI product management

Data platforms

Semantic layer

RAG embeddings

Education

Bachelor's degree in CS or related

Tools

SQL

dbt Semantic Layer

Cube

Job description

About the Team/Role:

At WEX, context engineering is the discipline of turning collective company knowledge, operational reality, and business logic into trusted, timely, and permission‑aware context for AI agents. As a Senior AI Product Manager (Context Engineering), you will own the enterprise context layer that powers WEX's global fleet of AI agents. In this hands‑on builder role within our Data, AI, Risk & Product organization, you will bridge unstructured knowledge, governed semantic data, and agent execution workflows, partnering directly with global engineering, data, and business teams to ensure every AI action is grounded, authorized, and accurate.

How you'll make an impact:

• Strategy & Portfolio: Partner with global product, engineering, and business leaders to prioritize high‑value context initiatives, sequencing workflows based on business impact, agent demand, source readiness, and risk.


• Governed Semantic Layer & NL‑to‑SQL: Own the semantic object roadmap for core enterprise entities (e.g., accounts, claims, plans), defining certified measures, join graphs, and Row‑Level Security (RLS) to replace raw schema reasoning and eliminate hallucinations.


• Retrieval & Grounding: Establish enterprise standards for federated ingestion, chunking, caching, metadata, and citation enforcement, consolidating legacy knowledge APIs into unified, multi‑tenant interfaces.


• Workflow Context Packs: Design and deliver production‑ready context packs for critical operational workflows and SOPs, partnering directly with agent teams to inspect retrieval traces, debug failures, and optimize context consumption.


• Quality & Benchmarks: Build and run rigorous evaluation harnesses, golden datasets, error taxonomies, and go/no‑go quality gates to benchmark retrieval relevance, query precision, and agent containment.


• Governance & Value Realization: Embed auditability, data lineage, least‑privilege access, and responsible AI guardrails into the context layer by design, tracking ROI through API cost reduction, task resolution lift, and operational risk mitigation.

Experience you'll bring:

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


• Experience: Senior‑level Product Management experience owning data platforms, enterprise search/retrieval systems, semantic layers, API products, or internal developer platforms consumed by engineering teams.


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


• Data Modeling & SQL: Strong experience working with structured enterprise data, relational models, certified metrics, and the failure modes of natural‑language querying over raw database schemas.


• Hands‑on Technical Depth: Demonstrated comfort working directly with technical artifacts—inspecting retrieval traces, reading SQL query plans, reviewing JSON/YAML configurations, and executing API calls.


• AI Evaluation & Benchmarking: Proven track record of designing and running evaluation harnesses, golden benchmark datasets, error taxonomies, and quantitative quality gates.


• Security & Governance: Solid working knowledge of enterprise controls, including authentication/identity, tenant isolation, Row‑Level Security (RLS), audit logging, and data privacy.


• Communication & Influence: Exceptional written and verbal communication skills in English, with a demonstrated ability to align and influence global engineering, security, compliance, and executive stakeholders without direct authority.

What will give you an edge:

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


• Hands‑on familiarity with headless BI, metric stores (e.g., dbt Semantic Layer, Cube), or governed NL‑to‑SQL products.


• Domain background in payments, fintech, benefits, healthcare‑adjacent platforms, or other highly regulated environments.


• Experience with vector databases, automated RAG evaluation frameworks (e.g., Ragas, TruLens), or agent tool protocols (e.g., Model Context Protocol - MCP).


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

The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non‑sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well‑being.

• Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more.


• Most sales positions are eligible for commission under the terms of an applicable plan.


• Non‑sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan.


• WEX's comprehensive and market competitive benefits are designed to support your personal and professional well‑being.

Pay Range: $125,300.00 - $154,100.00