The Senior Agentic Systems Engineer is a hands-on engineer who designs, builds, and operates AI-powered tools and workflows for engineering teams.
Were looking for builders who are not only users of AI tools, but can design autonomous agentic systems, optimize model usage, create reusable agents and workflows, and orchestrate complex multi-step work across multiple tools and agents.
Youll be a one-person-army builder: able to understand a problem, define the approach, build the backend, create a simple UI when needed, integrate APIs, connect agents, automate workflows, and deliver working tools quickly.
How will you make an impact?
Build centralized AI-powered tools for engineering teams.
Create and maintain agents, skills, hooks, MCP servers, plugins, and workflow automation.
Design autonomous agentic systems for internal engineering use cases.
Build multi-step AI workflows across code, documentation, Jira, GitHub, CI/CD, and internal systems.
Build tools for PR review support, test generation, documentation updates, spec creation, codebase understanding, and developer productivity.
Learn from local teams and convert successful solutions into reusable centralized assets.
Integrate AI tools with GitHub, Jira, Confluence, CI/CD, internal portals, and engineering systems.
Optimize AI workflows for cost, latency, quality, and reliability.
Apply token economy thinking when designing agents, prompts, MCP usage, RAG flows, and tool integrations.
Contribute to the internal AI marketplace and reusable asset catalog.
Work directly with engineering teams, collect feedback, and iterate quickly.
Requirements: Strong practical experience with LLMs and AI-assisted development.
Experience designing, building, and orchestrating autonomous agentic systems and multi-agent workflows for internal or external automation.
Experience with agents, skills, MCP servers and development, plugins, RAG, embeddings, and AI orchestration frameworks.
Ability to orchestrate complex, multi-step work across cooperating agents and tools.
Deep understanding of token economy, model selection, prompt/context design, and AI workflow optimization for cost, latency, speed, quality, accuracy, and reliability.
Deep, current knowledge of the AI tooling and coding-agent ecosystem, such as Claude Code, GitHub Copilot, Cursor, Codex, or similar.
Experience with telemetry, dashboards, and AI usage analytics.
Strong hands-on software engineering experience.
Full-stack capability: backend, APIs, automation, and basic frontend when needed.
Experience building internal tools, developer tools, automation platforms, productivity solutions, CLI tools, internal plugins, developer portals, or internal marketplaces.
Experience integrating with GitHub API, Jira API, Confluence API, and CI/CD systems.
Proficiency in TypeScript, Node.js, Python, React, or similar modern technologies.
Strong product sense and ability to translate engineering pain points into practical tools and solutions.
Ability to design, deliver, and own working solutions independently.
Comfortable working with ambiguity and rapidly evolving technologies.
This position is open to all candidates.