Senior AI Software Engineer

Placer.ai

13h•$160,000 - $190,000•Remote

About The Position

Placer.ai is building out PlacerX, the AI agentic and context layer used to run the company internally. This platform includes tooling, integrations, agents, and automation designed to enhance team efficiency. As a Senior AI Software Engineer, you will be instrumental in building this platform from the ground up, focusing on agents, connectors, automation, and infrastructure to drive significant productivity gains across the company. A key aspect of this role involves developing the use of Claude and Databricks, which currently form the backbone of the internal AI stack. Every employee already utilizes Claude and Databricks BI for analysis, automation, and research, and the demand for deeper integrations is rapidly increasing. You will be responsible for advancing these capabilities, moving beyond basic usage to implement genuinely agentic, high-leverage workflows embedded throughout the business. This is a hybrid role combining platform engineering with internal-facing integration leadership. You will report to the COO and collaborate with teams such as AI Operations, R&D, Data Science, and GTM, managing the entire process from integration requests to production-ready systems. Additionally, you will contribute to building a triage and review process to enable safe self-service for the broader organization. This is an opportunity to build the AI backbone of a rapidly growing company and see your work adopted by hundreds of people quickly.

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, including Google Cloud auth patterns (gcloud, service accounts)
Experience building and deploying services to Kubernetes or equivalent container infrastructure
Familiarity with Databricks or similar DW/DLs is a plus
Comfort working without an existing playbook; role definition, standards, and tooling will evolve
Strong communication skills; ability to translate between business requests and engineering requirements
Comfortable navigating competing priorities across R&D Architecture, AI Enablement, and business teams

Nice To Haves

Demonstrated use of AI tools to work more efficiently—whether professionally or personally—and a curiosity for finding new ways to apply them.
Comfort integrating generative AI into day-to-day workflows to boost productivity, quality, and output.

Responsibilities

Architect agents that perform work by chaining reasoning, tool calls, and decision-making into reliable multi-step workflows, including autonomous or human-in-the-loop operation.
Provide agents with secure, governed access to necessary systems and data through MCP servers, function/tool interfaces, and retrieval over internal knowledge.
Design, build, and deploy MCP servers for both external SaaS integrations (e.g., Google Analytics, Search Console) and custom internal tools.
Build the OAuth and credential management layer for secure, scalable connector authentication, implementing reusable patterns for adoption.
Collaborate with R&D Architecture to define and enforce production-ready standards for Placer MCP servers (security, deployment, logging, access controls).
Triage incoming connector requests and bug reports, prioritizing rollout-critical items and clarifying self-service options.
Build and maintain Cowork plugins and Claude skills to extend Claude's capabilities for specific Placer workflows, automating manual processes.
Take ownership of Placer's internal BI environment on Databricks, including data restructuring, pipeline engineering, and preparing data for AI utilization.
Build and maintain tooling to track internal AI tool usage for leadership to measure adoption and identify high-value use cases.
Optimize compute, storage, and networking for the internal AI platform for performance and cost efficiency.
Implement security best practices for AI platforms, including identity management, encryption, and compliance monitoring.