Note: The job is a remote job and is open to candidates in USA. Asset Management Powered by AssetWorks USA is seeking a Staff AI Engineer to lead their team in transforming into AI-first development. This role involves designing AI-driven software development practices, mentoring developers, and ensuring the quality of AI-generated outputs.

Responsibilities

• Design and implement agentic development workflows - defining how AI agents are directed, evaluated, and governed across the team
• Establish quality engineering practices embedded in the development process
• Evaluate AI agent output for correctness, security, and architectural integrity - the team’s last line of defense
• Build and maintain AI-powered features, integrations, and internal tooling (LLM orchestration, MCP servers, observability)
• Define guardrails and risk governance for AI-assisted development - identifying one-way doors before agents walk through them
• Mentor developers on effective agent-directed workflows, prompt engineering, and critical evaluation of AI output
• Make architectural calls that AI agents cannot - system design, tradeoff analysis, cross-cutting concerns
• Drive test automation strategy and implementation as part of the development lifecycle, not as a separate function

Skills

• 7+ years software engineering experience with progressive technical leadership
• Demonstrated experience building agentic AI workflows, designing multi-step agent systems
• Experience with LLM orchestration, prompt engineering, and AI observability/evaluation frameworks
• Strong background in quality engineering or test automation - you've architected test frameworks from scratch
• Ability to evaluate AI-generated code for correctness, security issues, and architectural drift
• Experience leading or mentoring development teams through paradigm shifts
• Proficiency in at least one modern stack (TypeScript/Node.js, Python, C#/.NET, or similar)
• Solid understanding of CI/CD, automated testing pipelines, and release engineering
• Excellent communication - able to explain complex AI/engineering decisions to technical and non-technical stakeholders
• Experience with MCP (Model Context Protocol) or similar agent-tool integration patterns
• Background spanning both QA/test engineering and software development
• Experience with Angular, C#/.NET, or SQL Server (our stack)
• Cloud platform experience (Azure, GCP, or AWS)
• Familiarity with Playwright, Selenium, or similar E2E frameworks
• Experience establishing engineering practices across multiple squads or teams

Company Overview