AI Engineer

What You’ll Do

Craft & Delivery

Build and ship features of AI/ML and LLM-powered systems with guidance from senior engineers, contributing to solutions that run in production
Implement and maintain components of AI/ML and AI agent pipelines from data ingestion through model deployment, picking up the unglamorous parts as you grow
Contribute to LLM-powered features such as prompts, evaluations, retrieval, and tool integrations, working alongside senior engineers
Handle data preprocessing, feature engineering, and basic evaluation to prepare quality inputs and validate model and prompt performance

Collaboration & Communication

Work closely with engineers across a distributed, cross-functional team to move projects forward effectively
Document experiments, results, and model decisions clearly so findings can be built upon, replicated, and shared across the team
Participate in code reviews and team discussions, contributing your perspective and incorporating feedback

Leadership & Influence

Take ownership of assigned tasks and deliver end-to-end with consistency and follow-through
Share learnings from experiments and research with the broader team, contributing to a culture of continuous improvement
Bring intellectual curiosity to every problem — ask good questions, explore new approaches, and stay hungry to grow your craft

What You’ll Bring

3+ years of professional software engineering experience, with hands-on exposure to AI/ML systems and generative AI development
Solid software engineering foundation (Python or similar)
Foundational knowledge of cloud platforms (AWS, GCP, or Azure), with interest in deepening AWS and AWS GenAI expertise
Exposure to building or contributing to agentic AI systems alongside more senior engineers
Familiarity with AI frameworks and orchestration tools
Familiarity with evaluation and observability practices for LLM apps
Awareness of AI safety, responsible AI principles, prompt injection risks, and PII handling
Exposure to RAG pipelines: chunking strategies, embedding models, and vector databases
Experience building or integrating with APIs, including internal and third-party services
Awareness of LLM cost considerations such as token economics and caching strategies
Working knowledge of Docker for containerized deployments, with exposure to Kubernetes
Demonstrable, day-to-day usage of AI-forward coding tools such as Claude Code and Cursor

Helpful Extras and Unique Skills

You’ll Do Well Here if You Are

A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.
All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.
Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you.
Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.