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.
Specialized AI & Agentic Responsibilities
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.
Qualifications & Experience
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.
Human-in-the-Loop (HITL) : Understanding of how to build automated workflows that pause agent actions for human approval, ensuring safety and governance for autonomous systems.
CI/CD & Platform Ops Mastery (Core Focus)
GitOps & Continuous Delivery : Expert-level experience with GitOps workflows (e.g., ArgoCD or Flux ) to ensure that all platform configurations-including AI prompt templates and model parameters-are versioned, audited, and automatically reconciled.
Infrastructure-as-Code (IaC) at Scale : Mastery of Terraform. You don't just write scripts; you build modular, reusable libraries that enforce organizational security and cost-efficiency standards across hundreds of cloud accounts.
Modern CI Pipelines : Proficiency in designing complex pipelines (e.g., GitHub Actions, GitLab CI) that integrate automated testing, security scanning, and deployment gates for high-availability systems.
Unified Observability : Experience with OpenTelemetry (OTel) to build deep visibility into distributed systems. You focus on tracking both system performance and business-centric AI metrics (e.g., success rates of autonomous tasks).
Cloud P
Additional Information
Position Summary
As a Sr. Staff AI Platform Engineer , you are first and foremost a Systems Architect . Your mission is to design and build the high-performance software foundation that powers the enterprise. While your core expertise lies in distributed systems, cloud-native architecture, and platform engineering, you will apply these skills specifically to the "Context Layer"-the specialized infrastructure required to fuel next-generation Agentic AI workflows .
You will operate at the intersection of Systems Programming and Modern AI Infrastructure , solving "hard-tech" problems like real-time data orchestration, automated metadata evolution, and multi-cloud compute optimization. This is a "platform-as-a-product" role; you build the tools, SDKs, and engines that enable hundreds of other engineers to build autonomous agents with ease.
Wex · Remote