Senior AI Agent Engineer: Build Manny, the Scheduling AI

Planera; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Planera is building Manny, an AI scheduling assistant for construction. You’ll own the LangGraph/LangChain agent, prompts, and tool integrations, delivering reliable, observable AI features end to end.

You’ll work with the CTO and AI engineer to shape the architecture, control flow, and evaluation stack for production-grade performance. This role emphasizes hands-on software engineering, prompt design, and cross-functional collaboration to impact how schedulers work with AI on a modern CP M

Qualifications

• 4+ years of software engineering experience with production LLM features.
• Proficiency in Python for building production services.
• Hands-on experience with agentic LLM systems and tool calls.
• Experience with prompt engineering and tracing/observability.
• Familiarity with MCP or tool-function integrations for LLMs.
• Strong API design skills (REST, websockets, SSE).
• Excellent remote communication skills.

Responsibilities

• Design, build, and own Manny features end to end across backend, tools, and UI.
• Improve agent behavior and reliability via prompts and tool design.
• Evolve architecture: ReAct loops, routing, and streaming responses.
• Integrate LLMs across providers, balancing quality, latency, and cost.
• Extend Manny's tool surface through the MCP server.
• Build and own the evaluation loop with datasets and evaluators.
• Implement observability for agent runs with tracing and logs.
• Ensure safe, sandboxed execution of model-generated code.

Skills

Python

LLM features

Agentic systems

Prompt engineering

Observability

API design

Remote communication

LangGraph/LangChain

Education

Bachelor's degree in Computer Science

Tools

MongoDB

Redis

Docker

Go

Job description

Planera is building Manny, an AI scheduling assistant for construction. You’ll own the LangGraph/LangChain agent, prompts, and tool integrations, delivering reliable, observable AI features end to end.

You’ll work with the CTO and AI engineer to shape the architecture, control flow, and evaluation stack for production-grade performance. This role emphasizes hands-on software engineering, prompt design, and cross-functional collaboration to impact how schedulers work with AI on a modern CP M