Senior AI Software Engineer

placerlabs; United States; Remote; USD 160,000 - 190,000; Full time

Benefits offered by this job

Fully remote

Medical/dental/vision coverage

Job summary

You will design multi-step agents, secure access to systems, deploy integrations, and advance BI data usability in AI workflows. This fully remote role offers a competitive US base salary with equity potential.

Qualifications

• At least eight years of backend engineering experience.
• Experience with MCP servers, LLM tool use, or AI agent frameworks.
• Background in data engineering or analytics tooling.
• Strong understanding of REST APIs, OAuth 2.0, and credential management, including Google Cloud authentication patterns such as service accounts.
• Experience deploying services to Kubernetes or comparable container infrastructure.
• Strong communication skills and the ability to translate business requests into engineering requirements while balancing competing priorities.
• Comfortable working in a developing platform area where practices, standards, and tooling are still taking shape.

Responsibilities

• Design agents that carry out multi-step tasks using reasoning, tools, and decision logic, with autonomous or human-reviewed execution as appropriate.
• Build secure ways for agents to access business systems and internal knowledge, including tool interfaces, retrieval, and MCP servers.
• Develop and deploy integrations for external services and custom internal tools, connecting data sources through to user-facing workflows.
• Improve internal AI and analytics capabilities, including making business intelligence data more usable by AI workflows.
• Build usage tracking so teams can understand adoption and identify valuable use cases.
• Improve platform performance and cost efficiency, and implement identity, encryption, audit, and compliance safeguards.

Skills

Backend engineering

MCP servers

LLM tool use

Data engineering

REST APIs/OAuth2

Kubernetes

Communication

Job description

Role overview

Build an internal AI platform that helps teams automate recurring work and use company data and tools through reliable, governed workflows. This senior engineering role spans agent design, integrations, and production infrastructure, from evaluating an internal request through deployment. You will work across technical and business teams as the platform and its standards develop.

Responsibilities

• Design agents that carry out multi-step tasks using reasoning, tools, and decision logic, with autonomous or human-reviewed execution as appropriate.
• Build secure ways for agents to access business systems and internal knowledge, including tool interfaces, retrieval, and MCP servers.
• Develop and deploy integrations for external services and custom internal tools, connecting data sources through to user-facing workflows.
• Improve internal AI and analytics capabilities, including making business intelligence data more usable by AI workflows.
• Build usage tracking so teams can understand adoption and identify valuable use cases.
• Improve platform performance and cost efficiency, and implement identity, encryption, audit, and compliance safeguards.

Requirements

• At least eight years of backend engineering experience.
• Experience with MCP servers, LLM tool use, or AI agent frameworks.
• Background in data engineering or analytics tooling.
• Strong understanding of REST APIs, OAuth 2.0, and credential management, including Google Cloud authentication patterns such as service accounts.
• Experience deploying services to Kubernetes or comparable container infrastructure.
• Strong communication skills and the ability to translate business requests into engineering requirements while balancing competing priorities.
• Comfortable working in a developing platform area where practices, standards, and tooling are still taking shape.

Nice to have

• Familiarity with Databricks or similar data warehouse and lakehouse platforms.
• Practical use of AI tools and curiosity about applying generative AI to improve everyday workflows.

Benefits and work setup

• Fully remote role. The source lists a US annual base pay range of $160,000–$190,000, with actual offers depending on relevant experience, skills, education, credentials, location, and market data.
• Medical, dental, and vision coverage, flexible time off, a 401(k), and equity awards for some roles.