Staff Software Engineer, AI

WHO WE ARE

At Basis, we empower agencies and brands with cutting-edge software that automates digital media operations. Our all-in-one platform supports seamless planning, reporting, and financial reconciliation across direct, programmatic, search, and social media.

We’re not just building advanced technology; we’re also building a culture where passionate, motivated individuals come together to drive meaningful change. Our commitment to inclusivity and growth ensures our employees thrive both professionally and personally.

With our headquarters in Chicago, we offer flexible work options across the U.S. and Canada, including remote, hybrid, or on-site at headquarters.

ABOUT THE TEAM

Technology is at the core of what we do. The AI Core team at Basis Technologies builds Compass, the AI agent platform behind Basis. Compass agents plan and execute media planning, buying, and operations work on behalf of agencies and brands. We build the orchestration, tooling, and evaluation infrastructure that lets LLM-powered agents work reliably in a complex ad tech domain, and we expose the Basis platform to our own and our customers’ agents through MCP and A2A. The AI Core team also functions as an enabling team for all of Basis Engineering, developing the patterns and best practices for agentic and AI-assisted development that other teams build on.

WAYS YOU’LL CONTRIBUTE

As a Staff AI Engineer, you will be the technical lead for the AI Core team, specializing in the architecture and development of our agentic platform. Other ways you will contribute:

• Set the technical direction for Compass and our LLM-powered features. Architect multi-agent systems, own the major design decisions, and balance rapid experimentation with stable, scalable long-term architecture.

• Lead the design and evolution of the MCP servers, A2A integrations, and APIs that connect internal and external agents to the Basis media buying toolkit.

• Own agent orchestration, evaluation, and observability. Define how we measure agent quality and ensure agents reason, plan, and execute reliably in production. Own our software end to end, including production support for Compass.

• Serve as the team’s primary technical point of contact for Product, QA, Design, Operations, other Engineering teams, and relevant stakeholders. Represent the team in cross-team planning, architecture discussions, and RFCs.

• Drive large-scale technical projects that span multiple teams and systems, from ideation through production. Own team deliverables, decisions, quality, process, and technical direction. Develop a deep understanding of our business domain and stakeholder needs, translate business goals into realistic technical plans, and proactively identify risks and blockers.

• Own the team’s technical quality bar through design and code reviews. Onboard new engineers, mentor senior and mid-level engineers, and set a positive example on how to collaborate in pull requests, demos, and working relationships.

• Lead the adoption of AI-assisted and agentic development across Basis Engineering by establishing best practices and building the examples and infrastructure other teams adopt.

• Embody Basis’ core principles while fostering a positive culture within the team. Actively promote Basis in the community.

WHAT YOU BRING TO THE TABLE

• Minimum of 8 years of professional software engineering experience, including recent experience shipping production LLM-powered applications or agent systems.

• A track record of technical leadership, including owning the technical direction of a team or major system and influencing architecture beyond your immediate area of ownership.

• Expert-level proficiency in Python, with a history of architecting production APIs and backend services and integrating with protocols such as MCP and A2A.

• Deep experience building and operating production-grade agentic systems with frameworks such as Strands, LangChain, or the Claude Agent SDK, including asynchronous and event-driven patterns, prompt engineering, structured outputs, and techniques for improving agent reliability. Sound judgment on when to optimize for speed and when to invest in quality.

• Experience with evaluation and observability tools such as Langfuse or LangSmith, including designing evaluation strategies from the ground up.

• Fluency with AI coding tools (Claude Code, Cursor, Codex, etc.) as a core part of the development workflow, paired with strong judgme…