About this role
Placer.ai needs a Senior AI Software Engineer to build PlacerX, an internal AI agentic and context layer that automates repetitive workflows and connects tools across the company. Operating as part platform engineer and part internal-facing integration lead, this person will design and ship reliable multi-step agents, build custom MCP servers, and develop secure auth infrastructure. The engineer will report to the COO and collaborate closely with R&D, Data Science, GTM, and AI Operations teams. Ideal candidates bring strong backend engineering experience along with deep familiarity with AI agent frameworks, data platforms, and secure API integrations. They thrive in fast-paced environments where they can build production-grade systems from scratch and see their work adopted by hundreds of colleagues rapidly.
What you will do
- Architect autonomous multi-step agents that chain reasoning, tool calls, and decision-making logic to handle complex internal workflows.
- Design, build, and deploy external SaaS and custom internal MCP servers to provide secure, governed access to company data and systems.
- Implement robust OAuth and credential management layers to support secure connector authentication at scale.
- Develop and maintain Cowork plugins and Claude skills tailored to automate manual processes for specific business units.
- Restructure and clean up internal BI environments on Databricks to ensure data is optimized for AI consumption.
- Track internal AI tool adoption and optimize platform infrastructure for performance, security, and cost efficiency.
What you need
- Bring 8 or more years of backend engineering experience to the role.
- Demonstrate prior experience working with MCP servers, LLM tool use, or AI agent frameworks.
- Possess a solid understanding of REST APIs, OAuth 2.0, and credential management, including Google Cloud auth patterns.
- Show hands-on experience building and deploying services to Kubernetes or equivalent container infrastructure.
- Have prior experience in data engineering or analytics tooling.
- Communicate effectively to translate business requests into concrete engineering requirements while navigating competing priorities.
Nice to have
- Demonstrated use of AI tools to work more efficiently, whether professionally or personally.
- Curiosity for finding new ways to apply generative AI to boost productivity, quality, and output.
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
The position is listed as United States, Remote.
What is the salary range for this role?
The salary range is $160,000 to $190,000 USD.
Who does this role report to?
You will report to the COO and partner across AI Operations, R&D, Data Science, GTM, and other teams.