Software Engineer, AI Enablement

About

Architects and builds infrastructure and tooling that power AI agent development across the Software Development Lifecycle (SDLC). Develops production-grade agentic systems, orchestration frameworks, and observability solutions that enable teams to build, deploy, and monitor reliable AI agents at scale. Plays a key role in defining and implementing next-generation, AI-first SDLC practices through innovation and comprehensive instrumentation.

What We're Looking For

You demonstrate strong product sense for identifying high-impact automation opportunities, sound technical judgment in implementation decisions, and the ability to clearly articulate architectural trade-offs. You understand when AI agent solutions are appropriate versus simpler approaches and can confidently explain the reasoning behind design decisions.

You thrive in 0-to-1 and scaling environments, operating effectively in ambiguity where requirements evolve through experimentation and iteration rather than rigid upfront specifications.

Key Responsibilities AI Agent Development & Automation

• Develop production-grade AI agents that eliminate manual handoffs across the SDLC
• Create custom integrations and CLI tools that enable agents to understand internal systems and codebases
• Design comprehensive testing strategies to ensure agent reliability and output quality
• Implement standardized project scaffolding that embeds engineering best practices
• Build AI solutions that enhance code navigation, documentation, and developer workflows
• Identify workflow bottlenecks and deliver measurable impact through intelligent automation
• Drive evolution of the SDLC by identifying AI-first opportunities and validating outcomes through experimentation

Agent Infrastructure & Platform

• Architect and maintain production infrastructure supporting agent deployment, lifecycle management, and scalability
• Develop agent frameworks, templates, and SDKs that accelerate development
• Implement governed communication protocols for compliant agent-to-agent interactions
• Establish governance controls for agent behavior, permissions, and system access

Observability & Performance Analytics

• Design and implement metrics, monitoring, and logging infrastructure for AI agents and developer workflows
• Build dashboards that provide actionable insights into productivity, tool adoption, and agent performance
• Define KPIs and measurement frameworks to quantify automation impact
• Implement alerting and anomaly detection systems to ensure reliability
• Analyze telemetry data to identify optimization opportunities and inform strategic investment decisions

Collaboration & Impact

• Partner across teams to drive adoption of AI-powered tooling and process transformation
• Stay current with LLM technologies and promote AI-assisted development best practices
• Rapidly prototype solutions to validate use cases and demonstrate value
• Communicate data-driven insights through clear visualizations and reporting

Preferred Qualifications

• 5–7 years of software engineering experience building production systems
• Experience developing agentic systems using LLM orchestration frameworks
• Hands-on expertise with AI-powered development tools (code assistants, AI-enhanced editors)
• Strong understanding of SDLC, system design, and internal tooling development
• Experience with observability practices including metrics collection, logging frameworks, and dashboard development

Full-Stack Technical Proficiency

• Languages: Java, Python, JavaScript/TypeScript
• Frameworks: Angular, Spring Boot
• CI/CD platforms and cloud infrastructure (AWS)
• Monitoring and observability tools (e.g., Prometheus, Grafana, Cloud-native monitoring tools)
• Strong interest in transforming software development through AI-driven innovation and data-informed decision-making.