Position Overview We're looking for a Senior AI Engineer to design, build, and deliver production AI/ML systems. This role is ideal for an engineer with several years of experience who can confidently own features end-to-end, contribute to architectural decisions, and bring strong technical judgment to the problems they take on.
In this role, you will work as a key contributor on a cross-functional team, designing and implementing models, building the data pipelines and training workflows around them, and deploying systems to production environments. You'll be joining real, in-flight work where reliability, performance, and scalability matter. You'll collaborate with experienced engineers to enhance existing systems, deliver new capabilities, and contribute to the technical decisions that shape how our AI work scales over time.
What You'll Do Craft & Delivery - Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency
- Maintain and evolve AI systems in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability
- Bring an AI-forward coding mindset to your daily work, using tools like Claude and Cursor to ship higher-quality work at pace
Collaboration & Communication - Partner closely with product, engineering, and data teams to align AI work with broader product and business goals
- Translate technical tradeoffs, model behavior, and constraints into terms non-specialists can act on
- Participate actively in code reviews and design discussions, raising concerns and offering constructive feedback
Leadership & Influence - Contribute to AI architecture decisions with thoughtful perspective on tradeoffs and long-term implications
- Take ownership of meaningful work end-to-end, including the unglamorous parts of getting AI into production
- Raise the bar on engineering practices through your own work and by supporting more junior engineers when opportunities arise
What You'll Bring - 4+ years professional software engineering experience, with 2+ years focused on AI/ML systems in production and hands-on experience with generative AI development
- Strong software engineering background (Python or similar)
- Working knowledge of cloud platforms, preferably with in-depth understanding of AWS services and AWS GenAI offerings
- Proven ability to design and ship agentic systems
- Experience with AI frameworks and orchestration tools
- Experience with evaluation frameworks, and observability tools for LLM apps
- Understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling
- Hands-on experience building RAG pipelines: chunking strategies, embedding models, vector databases
- API development experience, including designing and integrating with internal and third-party services
- Cost optimization expertise: token economics, caching strategies, model routing, quantization
- Working knowledge of Docker and Kubernetes for containerized deployments
- Demonstrable, day-to-day usage and knowledge of AI-forward coding tools such as Claude Code and Cursor
- Strong problem-solving skills and the ability to navigate ambiguous technical challenges with sound judgment
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.
