Full-Stack Agentic AI Lead Developer Position Summary

Full-Stack Agentic AI Lead Developer What You Will Do

Agentic AI Development

• Design, develop, and deploy autonomous and semi-autonomous AI agent systems that interpret goals, gather context, select tools, and execute end-to-end workflows
• Build and maintain custom skills, plugins, and tool integrations that extend agent capabilities across enterprise environments
• Architect multi-agent orchestration patterns including agent-to-agent delegation, parallel task execution, and human-in-the-loop escalation paths
• Implement agentic memory frameworks, context management strategies, and guardrails that ensure reliable, safe, and auditable agent behavior
• Develop and refine system prompts, reasoning chains, and evaluation pipelines to continuously improve agent performance

Full-Stack Engineering

• Build robust, scalable web applications and APIs that serve as the interface and backbone for AI-powered solutions
• Work across front-end and back-end technologies to deliver complete, production-ready systems
• Design and implement data pipelines, integrations, and infrastructure to support agent operations at scale
• Write clean, maintainable, well-tested code and conduct thorough code reviews

Product Ownership & Business Alignment

• Own the product vision and roadmap for the AI solutions you build—from discovery through delivery and iteration
• Translate business objectives and stakeholder needs into prioritized backlogs, user stories, and acceptance criteria
• Collaborate directly with clients, executives, and cross-functional teams to define scope, manage expectations, and communicate progress
• Measure and report on product outcomes using business-relevant KPIs, not just technical metrics
• Make build-vs-buy and technology selection decisions grounded in ROI, time-to-value, and strategic fit
• Facilitate sprint planning, demos, and retrospectives—functioning as a player-coach who both builds and leads

Full-Stack Agentic AI Lead Developer Required Qualifications

Experience & Education

• 5–10 years of software development experience with progressive responsibility
• Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent practical experience)
• 2+ years of hands-on experience building AI-powered applications, including agent-based systems
• Demonstrated experience functioning as a product owner, product manager, or technical lead with direct business-facing accountability

Agentic AI & LLM Expertise

• Proven experience with agentic coding tools and AI-native development environments. Proficiency in one or more of the following is required:
  • Claude Code — terminal-native agentic development, sub-agents, skills authoring, MCP server integration
  • OpenAI Codex — autonomous cloud-based coding agents, background task execution, PR workflows
  • Cursor — AI-native IDE, multi-model routing, Composer multi-file editing, background agents
  • GitHub Copilot — agent mode, code review automation, workspace integration
• Experience building custom skills, tool definitions, and structured prompt architectures for AI agents
• Proficiency with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel
• Experience with agentic memory and context management (e.g., Mem0, Letta, custom RAG pipelines)
• Strong understanding of prompt engineering, chain-of-thought reasoning, and evaluation frameworks for agent behavior

Programming & Architecture

• Strong proficiency in Python and JavaScript/TypeScript; additional languages (C#, Go, Rust) are a plus
• Experience with front-end frameworks (React, Next.js, Angular) and back-end frameworks (FastAPI, Express.js, Flask)
• Expertise with Git, GitHub workflows, branching strategies, CI/CD pipelines, and infrastructure-as-code
• Experience building and consuming REST APIs, GraphQL endpoints, and microservices architectures
• Database expertise spanning relational (PostgreSQL), vector (Pinecone, Zilliz, Chroma), and graph databases (Neo4j)
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

Full-Stack Agentic AI Developer Preferred Qualifications

• Experience deploying LLM agents in production using serving frameworks such as vLLM, e2B, or Daytona
• Familiarity with Model Context Protocol (MCP) servers and building custom tool integrations
• Experience with agent evaluation, red-teaming, and safety testing methodologies
• Background in AI governance, responsible AI practices, or ISO 42001 / SOC 2 compliance frameworks
• Experience with AgentOps practices: monitoring, observability, and telemetry for autonomous systems
• Certified Scrum Product Owner (CSPO), SAFe Product Owner, or equivalent agile certification
• Prior Software product development, consulting or professional services experience with client-facing delivery accountability
• Mobile application development experience
• Experience mentoring junior developers and building team capability

What Sets You Apart