[Hiring] Senior Staff AI Platform Engineer @WEXWEXUS

Role Description

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.

Key Responsibilities

• AI Platform Strategy & Context Retrieval: Define and own the 3–5 year technical roadmap for our high-scale, AI-ready Data Lakehouse.
• Systems & Agentic R&D: Prototype and benchmark emerging trends in the AI ecosystem.
• Engineering Excellence: Set the gold standard for code quality, CI/CD, and system design across the organization.
• Specialized AI & Agentic Responsibilities:
  • Agentic Ecosystem Enablement: Design the platform-level interfaces required for Agentic workflows.
  • Contextual Infrastructure: Build the "Context Fabric" that allows AI agents to securely discover, access, and interpret enterprise data.
  • Protocol & Trend Standardization: Implement and advocate for emerging standards like the Model Context Protocol (MCP).

Qualifications

• Expert Software Engineering: 15+ years in software engineering.
• Systems Architecture: Deep experience building extensible frameworks, high-throughput APIs, and libraries.
• Agentic Development & Emerging Trends (Specialized Plus):
  • Agentic Design Patterns: Hands-on experience with Multi-Agent Orchestration.
  • Protocol Interoperability: Knowledge of the Model Context Protocol (MCP).
  • AI-Ops Integration: Experience building "AI-native" CI/CD features.
  • Human-in-the-Loop (HITL): Understanding of automated workflows for human approval.
• CI/CD & Platform Ops Mastery (Core Focus):
  • GitOps & Continuous Delivery: Expert-level experience with GitOps workflows.
  • Infrastructure-as-Code (IaC) at Scale: Mastery of Terraform.
  • Modern CI Pipelines: Proficiency in designing complex pipelines.
  • Unified Observability: Experience with OpenTelemetry (OTel).
• Cloud Platform Expertise (AWS & Azure):
  • Cloud Console & Service Mastery: Deep proficiency in AWS and Azure Management Consoles.
  • Cloud-Agnostic Abstraction: Proven ability to build platform layers that bridge AWS and Azure.
  • Governance & Cost Optimization: Experience using cloud-native tools.
• Leadership & Education:
  • Influence: A proven track record of "leading by influence."
  • Communication: Ability to communicate complex architectural trade-offs.
  • Education: Bachelor’s or Master’s degree in Computer Science preferred.

Requirements

• 15+ years in software engineering.
• Expert in Java or Scala (distributed systems focus) and Python.
• Deep experience building extensible frameworks and high-throughput APIs.

Benefits

• Health, dental and vision insurances.
• Retirement savings plan.
• Paid time off.
• Health savings account.
• Flexible spending accounts.
• Life insurance.
• Disability insurance.
• Tuition reimbursement.
• Quarterly or annual bonus based on role and applicable plan.

Pay Range

$220,000.00 - $255,800.00