Full stack Engineer- AI Augmented Engineer - Local to DMV Areas - Independent candidate F2F
About The Position
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. 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.
Requirements
- 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)
Responsibilities
- 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
- 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
- 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
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
