About the Role
This role is for a hands-on technical leader responsible for shaping and building the core infrastructure of a production AI platform, including media processing, LLM routing, distributed data systems, agentic AI, and observability. You will define architectural direction, write code, and make critical technical decisions while collaborating across product and engineering teams. The position demands deep systems thinking, ownership from concept to deployment, and a focus on long-term scalability and real-world performance.
Responsibilities
- Lead the foundational infrastructure by defining technical strategy and designing core systems including media pipelines, LLM routing, distributed data architectures, and observability tools from the ground up.
- Develop AI agent frameworks and multi-agent ecosystems, including orchestration logic, tool integration, MCP server deployment, A2A dispatch mechanisms, and production-grade reliability controls.
- Tackle complex distributed systems challenges involving data flow management, fault isolation, consistency trade-offs, and sustained performance under heavy load.
- Establish robust reliability standards by integrating observability early—implementing tracing, metrics collection, and structured logging—to support rapid iteration without compromising system integrity.
- Influence platform evolution by contributing engineering insights to strategic planning, helping determine priorities, sequencing, and technical justification for new initiatives.
Benefits
- Comprehensive benefits
- Generous access to frontier and open-weight models for day-to-day work, prototyping, and evaluations
- Fully remote role
Compensation
Competitive compensation
Work Arrangement
Remote (Worldwide)
Team
Small, senior group of scientists and veteran engineers focused on solving hard problems with immediate user impact
About the Role
The AI Systems Architect will lead the technical vision for the core infrastructure powering the production AI platform, including media pipelines, LLM routing, distributed data systems, agentic AI, and observability. This is a hands-on, greenfield role requiring deep technical ownership—from setting architectural direction to writing code and making pivotal decisions. You will work closely with product and engineering teams to shape what gets built and how, ensuring systems are reliable, observable, and scalable under real-world load. Your early decisions will have long-term impact. We value engineering craft and seek someone who understands failure modes in production and can establish foundations that allow fast iteration without sacrificing quality.
How we're different
Unlike many AI tools stuck in demo phases, our systems are used daily by expert teams making real business decisions with measurable financial impact. We are a lean, experienced team of scientists and engineers from top-tier tech and consumer companies, focused on solving hard problems with immediate user feedback. We move quickly—prototypes can become live products in days. Our advantage starts with proprietary data and proven methodologies behind billions in ad spend. We build internally, validate at scale, and release what works. Speed trumps perfection until a solution proves it can scale.
