Product Manager - AI Capabilities

WEX-posted 4 days ago

$94,000 - $125,000/Yr

Full-time • Mid Level

Portland, ME

5,001-10,000 employees

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WEX is seeking a highly technical and results-oriented Product Manager to lead the development of our shared AI capabilities. This is a role for a builder. We are looking for a PM who is comfortable opening a code editor to prototype an idea before writing a PRD. In this role, you will own the lifecycle of autonomous AI agents—from defining the persona and tool capabilities to actively building the proof-of-concepts (POCs) that validate feasibility. You will bridge the gap between business needs and engineering reality, designing AI-powered solutions that serve our diverse lines of business.

Technical Discovery & Prototyping (The "Builder" Aspect)
Hands-on Validation: Instead of just defining requirements, you will build functional prototypes (using Python, LangChain, or direct LLM API calls) to validate if a use case is solvable by current models.
Prompt Engineering & Logic: You will own the initial system prompts and logic flows. You understand how to structure inputs to ensure the agent follows instructions and outputs structured data (JSON).
Feasibility Analysis: Translate customer insights into technical hypotheses. You will determine the trade-offs between model intelligence (e.g., GPT-4o) vs. latency and cost (e.g., Llama 3) for specific features.
Agent Architecture & Execution
Define Agent Capabilities: specificy the "tools" the AI needs to interact with (e.g., specific internal APIs, SQL databases, or vector stores) to solve the user's problem.
Drive Complex Initiatives: Lead the transition of your prototypes into production-grade software by collaborating with engineering to handle edge cases, rate limits, and security guardrails.
RAG & Context Management: Design how the product retrieves information. You will make decisions on what context needs to be injected into the model to prevent hallucinations.
Data, Evals & Performance
LLM Evaluation: Define success beyond just "user happiness." You will implement evaluation frameworks ("Evals") to quantitatively measure agent accuracy, hallucination rates, and successful tool usage.
Insight-Driven Decisions: Use observability tools (like LangSmith or Datadog) to review conversation traces and identify where the AI logic is failing.
Collaboration & Influence
Engineer-to-Engineer Communication: You speak the language of the developers. You can conduct code reviews on the logic layer and discuss API specifications for tool calling.
Stakeholder Education: Demystify AI for non-technical stakeholders (Digital, Commercial teams), clearly explaining what the technology can and cannot do to manage expectations effectively.

Technical Proficiency: Fluency in Python . You must be able to write scripts to test APIs, manipulate data, and interact with LLMs.
Builder Experience: Proven experience building an AI application, chatbot, or agent (side projects count). You have hands-on experience with OpenAI/Anthropic APIs and frameworks like LangChain or LlamaIndex .
Product Experience: Minimum of 2+ years in product management. You know how to prioritize a roadmap, manage a backlog, and focus on business value.
Data Fluency: Ability to write SQL queries to pull your own data and analyze product usage.

Experience with Vector Databases (Pinecone, Weaviate) and RAG (Retrieval Augmented Generation) architectures.
Experience fine-tuning models for specific tasks.
A Computer Science degree or equivalent software engineering background.

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

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