Planera
Senior AI Agent Engineer
United States · Senior
Sponsorship not specifiedDetected 23 days ago
PythonGoReactNode.jsFlaskGitMongoDBRedisVector DatabasesAWSGCPDockerTerraformCI/CDAPI DevelopmentRESTWebSocketsLLMsRAGAgentic AILLMOpsLangGraphAI OrchestrationProject Management
About the role
- This is a hands-on applied AI role with a strong software engineering foundation and a focus on reliability, behavior quality, and user impact.
Responsibilities
- Design, build, and own Manny features end to end across the agent backend, tools, and UI
- Improve agent behavior, reliability, and answer quality through prompt engineering, tool design, and changes to the agent control flow
- Design and extend Manny's tool surface through the MCP server that connects the agent to Planera's scheduling services
- Build and own the evaluation loop: golden datasets, automated evaluators, snapshot-based replay, and offline and online quality metrics
- Implement observability for agent runs with tracing, metrics, and structured logging, and use it to debug and improve behavior in production
- Collaborate with product, backend, and frontend to deliver AI features end to end
- 4+ years of software engineering experience, including recent hands-on work building production LLM features.
- Hands-on experience building agentic systems with LLMs: tool and function calling, ReAct or similar loops, and orchestration frameworks such as LangChain/LangGraph
- Build the AI that changes how the world plans and schedules construction.
Requirements
- Strong proficiency in Python building production services
Nice to have
- Experience with the Model Context Protocol (MCP) or building tool and function-calling integrations for LLMs
- Product mindset with a focus on user impact and pragmatic tradeoffs
- Experience with MongoDB and Redis
- Cloud experience (AWS or GCP), containers, and CI/CD
- Go experience, as most of our backend systems are written in Go, including the MCP tool server
- Practical experience with retrieval and augmentation (RAG), embeddings, and vector stores
- Familiarity with LangSmith or comparable LLM evaluation and tracing platforms
- Frontend or React familiarity for agent UI work
Skills
- Python (Flask), Go, LangGraph/LangChain, LangSmith, MongoDB, Redis, S3, REST/websockets/SSE, Docker, AWS/GCP, Terraform, GitLab CI/CD
- tool and function calling, ReAct or similar loops, and orchestration frameworks such as LangChain/LangGraph
- shaping model behavior reliably, debugging failures from traces, and managing large prompts and token cost
Compensation
- Competitive salary, stock options, benefits package, and a dynamic work environment.
Benefits
- Competitive salary, stock options, benefits package, and a dynamic work environment.
Company info
- Join a smart, spirited team dedicated to innovation and excellence.
- Growth: Opportunity for professional growth and career advancement in a fast-paced start-up environment.
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This listing is sourced directly from Planera's careers page and normalized into a canonical job model.