Senior Software Engineer, AI Tooling & Enablement

Austin, TX

Work Model:

Hybrid, 2 to 3 days in office

Compensation:

$180,000 base salary

Employment Type:

Full-time

(Recruiting for our client, a leader in the software space)

We are hiring a

Senior Software Engineer, AI Tooling & Enablement

to help build and scale AI-powered engineering workflows across a large software environment.

This is a hands-on implementation role for someone with a strong software or quality engineering background who has already built and deployed AI agents, workflows, and developer tools in real production environments.

Key Responsibilities

• Design and implement AI agents, multi-agent systems, skills, and workflow automation.
• Embed AI into software development, code review, testing, defect analysis, documentation, and developer productivity workflows.
• Evaluate AI models based on capability, cost, latency, security, and business use case.
• Build prompt versioning, regression testing, and change management frameworks for AI workflows.
• Monitor AI infrastructure costs and identify opportunities to improve token efficiency.
• Implement safeguards around prompt injection, PII exposure, data leakage, and responsible AI usage.
• Build observability into AI agent workflows.
• Create and deliver internal AI training for engineering teams.
• Partner with product and engineering teams to continuously improve AI tools based on real-world usage.

What We’re Looking For

• 5+ years of experience as a software engineer, quality engineer, architect, or similar.
• 1+ year of hands-on experience building AI agents or AI-powered workflows in production.
• Experience with tools and technologies such as Claude Code, MCP, multi-agent orchestration, CodeRabbit, or similar platforms.
• Experience integrating AI into software development, code review, test generation, CI/CD, or developer tooling.
• Strong understanding of model selection, prompt engineering, cost optimization, and AI security.
• Familiarity with RAG pipelines, vector databases, MCP servers, or AI observability is an asset.
• Experience training or enabling engineering teams on AI development practices.

Candidates must be authorized to work in the United States without current or future employer sponsorship.