Full-Stack Agentic AI Lead Developer (Hybrid with travel)
with Product Ownership Responsibilities Full-Stack Agentic AI Lead Developer Position Summary We are looking for a Full-Stack Agentic AI Developer who can build autonomous, goal-driven AI systems and ship them as products that solve real business problems. This is not a traditional developer role. The ideal candidate blends deep technical fluency in agentic frameworks and AI-native development tools with a product owner’s instinct for prioritization, stakeholder management, and outcome-driven delivery.
You will design, build, and orchestrate multi-agent systems that plan, reason, use tools, recover from errors, and collaborate with humans when the stakes are high. Equally important, you will own the product roadmap for the solutions you build—translating business objectives into technical requirements, managing backlogs, and ensuring what ships creates measurable value. 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 The best candidate for this role doesn’t just write code—they think in systems, products, and outcomes. You understand that the highest-value AI work often happens upstream of production: in defining the right problem, designing the right agent architecture, and ensuring the solution actually moves a business metric. You are equally comfortable whiteboarding an agent orchestration pattern with engineers and presenting a product roadmap to a C-suite audience.
You have strong opinions, loosely held, about how autonomous AI systems should be built, tested, and governed. You stay current not because you’re told to, but because you’re genuinely fascinated by the pace of change in agentic AI—and you bring that energy to your team every day.

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