Sr Staff AI Platform Engineer

WEX Inc.
South Portland, ME, United States
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

LangGraph Framework Training Data Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Architectural Patterns Software Quality Continuous Integration Data Security Software Design Patterns Distributed Systems Interoperability
+14 more
Python (Programming Language) Language Modeling Software Engineering Systems Architecture Enterprise Data Management Retrieval-Augmented Generation Large Language Models Multi-Agent Systems Agentic-AI AI Platforms CrewAI Virtual Agents Model Context Protocol Human in the Loop

Job description

  • AI Platform Strategy & Context Retrieval: Define and own the 3-5 year technical roadmap for our high-scale, AI-ready Data Lakehouse. This platform must be explicitly optimized for AI Agent operations and efficient context retrieval, delivering low-latency, high-throughput data access essential for vector databases and LLM-driven applications.
  • Systems & Agentic R&D: Prototype and benchmark emerging trends in the AI ecosystem. You will evaluate next-generation architectural patterns such as Multi-Agent Orchestration, autonomous long-term memory management, and specialized Agent Evaluation frameworks to ensure the platform remains at the cutting edge.
  • Engineering Excellence: Set the gold standard for code quality, CI/CD, and system design across the organization. You will lead cross-functional architecture reviews and serve as the final escalation point for the most complex technical bottlenecks., * Agentic Ecosystem Enablement: Design the platform-level interfaces required for Agentic workflows, focusing on standardized "Host-to-Server" communication and tool-execution environments. This includes building robust "Human-in-the-Loop" (HITL) triggers and fail-safe mechanisms for autonomous actions.
  • Contextual Infrastructure: Build the "Context Fabric" that allows AI agents to securely discover, access, and interpret enterprise data. You will architect systems that move beyond basic search into Reasoning-based Retrieval, where the platform understands the intent behind an agent’s query.
  • Protocol & Trend Standardization: Implement and advocate for emerging standards like the Model Context Protocol (MCP) to ensure interoperability. You will stay ahead of trends such as Small Language Models (SLMs) for edge-compute and Agentic RAG, ensuring the platform can pivot as the industry evolves.

Requirements

  • Software Engineering Foundation
  • Expert Software Engineering: 15+ years in software engineering. You are an expert in Java or Scala (distributed systems focus) and Python.
  • Systems Architecture: Deep experience building extensible frameworks, high-throughput APIs, and libraries used by other developers. You prioritize building "software-defined infrastructure" over manual configuration.
  • Agentic Development & Emerging Trends (Specialized Plus)
  • Agentic Design Patterns: Hands-on experience with the latest trends in agent development, such as Multi-Agent Orchestration (using frameworks like LangGraph or CrewAI) and the transition from static RAG to Agentic RAG.
  • Protocol Interoperability: Knowledge of the Model Context Protocol (MCP) and other emerging standards that allow AI agents to interact with diverse data sources and tools in a plug-and-play manner.
  • AI-Ops Integration: Experience building "AI-native" CI/CD features, such as automated LLM-based evaluations (evaluating agent reasoning paths in the build pipeline) and Automated Root-Cause Analysis for system failures.

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