Senior AI Software Engineer
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Job Description
Senior AI Software Engineer building Placer.ai’s internal AI platform. Creating agents, MCP integrations, and Databricks automation for the location analytics company’s teams.
Responsibilities:
- Architect AI agents that execute reliable multi-step workflows using reasoning, tool calls, and decision-making
- Design, build, and deploy MCP servers for external SaaS integrations and Placer.ai internal tools
- Build secure OAuth and credential-management infrastructure for connector authentication
- Define and apply production-readiness standards for MCP servers, including security, Kubernetes deployment, logging, and access controls
- Triage connector requests and bug reports and distinguish rollout-critical work from backlog
- Build and maintain Cowork plugins and Claude skills for Marketing, Operations, Data, and other workflows
- Automate manual and repetitive processes using Claude
- Own and improve Placer.ai’s internal Databricks BI environment, including data restructuring and ingestion pipelines
- Build tooling to track internal AI usage, adoption, and high-value use cases
- Optimize compute, storage, networking, performance, and cost across the internal AI platform
- Implement AI platform security practices including identity management, encryption, and compliance monitoring
- Partner across AI Operations, R&D, Data Science, GTM, and other teams
- Report to the COO and own the path from integration request to production-grade system
- Help establish triage and review processes enabling safe self-service across the organization
Requirements:
- 8+ years of backend engineering experience
- Prior experience with MCP servers, LLM tool use, or AI agent frameworks
- Prior experience in data engineering or analytics tooling
- Solid understanding of REST APIs, OAuth 2.0, and credential management
- Experience with Google Cloud authentication patterns, including gcloud and service accounts
- Experience building and deploying services to Kubernetes or equivalent container infrastructure
- Familiarity with Databricks or similar data warehouses/data lakes is a plus
- Comfort working without an existing playbook and adapting as role definition, standards, and tooling evolve
- Strong communication skills for translating business requests into engineering requirements
- Ability to navigate competing priorities across R&D Architecture, AI Enablement, and business teams
- Demonstrated use of AI tools and curiosity about applying them in new ways
- Comfort integrating generative AI into day-to-day workflows
- No educational credential explicitly required
Benefits:
- Competitive salary
- Excellent benefits
- Fully remote
- Medical coverage
- Dental coverage
- Vision coverage
- Flexible time off
- 401K
- Equity awards for certain roles
- Opportunity to work with and learn from top-notch talent
- Central and critical role at Placer.ai
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