Senior Engineer: Agent Academy

Focused Labs•Chicago, IL

11d•Hybrid

About The Position

This role would play a crucial role in shaping and implementing engineering best practices and ensuring the successful delivery of complex software projects. With clients, we develop trust and influence - we are unintimidated and unintimidating. With colleagues, we set the standard for how we deliver success for clients.

Requirements

You're a hands-on, full stack engineer with a strong track record of delivering software in collaborative, agile environments.
You're proficient in Python and/or JS/TypeScript (Ruby or similar works too) and have solid OOP and design fundamentals.
You understand async/await and the event loop as well as thread-based concurrency, and you know when to use which.
You believe that code quality matters, and that TDD and pairing help build better systems and stronger teams.
You're comfortable with unit and integration tests, regression suites, and CI gates.
You know your REST fundamentals (HTTP verbs, status codes, CORS) and have modeled data with ORMs like SQLAlchemy, Django ORM, ActiveRecord, or Prisma.
You can jump into an existing React, Vue, or Svelte frontend and ship changes, with or without a coding agent.
You've deployed containerized apps to a cloud provider and have a working understanding of IAM, scaling, logging, and observability.
You've worked directly with clients or product stakeholders and can explain technical work in language anyone can understand.
You're excited about what's happening in the AI space but stay focused on delivering value.
You love to share what you're learning and make the team around you better.

Nice To Haves

Exposure to LLM APIs or agent frameworks
Experience building AI-enabled applications with LangChain and LLMs that deliver production-ready outcomes for clients
Hands-on experience with LangChain, LangGraph, and LangSmith

Responsibilities

Writing lots of code
Delivering features end to end across the stack, from backend services and APIs to modern web UIs.
Pair program daily with teammates and clients to share knowledge, improve code quality, and grow together.
Practice TDD and continuous refactoring to ensure code is reliable, maintainable, and understandable.
Build APIs with FastAPI, Express, or similar, with clear schemas and validation using tools like Pydantic, JSON Schema, or zod.
Containerize, deploy, and monitor apps in the cloud using Docker, CI/CD pipelines, and observability tools like Honeycomb or Datadog.
Collaborate closely with designers, product managers, and stakeholders to continuously deliver valuable software.
Help define metrics and run experiments, including A/B tests, so we know what's actually working.
Stay curious through experimenting with new patterns in the GenAI space, share what works (and what doesn't), and help evolve how we build AI-powered software.