Note: The job is a remote job and is open to candidates in USA. TaskRay is on a mission to ensure businesses get off to a great start with a flawless customer experience once the opportunity is marked Closed Won. The Senior AI Engineer will build production agent capabilities for TaskRay's AI platform, working closely with the product team to develop features that enhance customer success and operational efficiency.
Responsibilities
- Build production agent capabilities for our PM Agent (the internal-facing agent that maintains live project status and increases customer team productivity), our Execution Agent (the internal-facing agent that completes tasks on behalf of human counterparts), and our External Onboarding Agent (the customer-facing agent that handles status, document collection, and end-customer interaction)
- Contribute to our MCP server, the platform layer that connects these agents to TaskRay's project, customer, and onboarding data
- Design prompts, agent loops, and tool integrations that meet customer-grade reliability, not demo-grade
- Own subsystems end to end: retrieval pipelines, eval harnesses, prompt libraries, tool registries, and the observability around them
- Partner with design partner customers to ship custom agent workflows that teach us what to productize. Engagements run via video and shared tooling, not on-site
- Translate customer-specific work into reusable building blocks for the core platform
- Partner with Product on customer-facing demos, walkthroughs, and feedback loops
- Help build and maintain the MCP server and the off-platform service layer that hosts our agent capabilities
- Develop integrations with adjacent systems where the agents need them (Google Drive, calendar and meeting transcripts, document stores, CRM data)
- Contribute to the eval, observability, and reliability infrastructure our Staff engineer is establishing
- Write clean, well-documented code that your teammates will thank you for
- Participate in code reviews with a constructive, growth-oriented mindset
- Actively contribute to our agentic coding standards and norms
Skills
- You have shipped LLM-based features to production users. You have lived through the gap between a working demo and a system that actually serves customers
- Hands-on experience with retrieval pipelines, agent loops with tool use, and the evals that keep them honest
- Strong Python proficiency (the lingua franca of the AI stack), with production experience deploying real systems
- Hands-on experience integrating LLM provider APIs (Anthropic Claude, OpenAI, or equivalent) into real applications, including evals, prompt iteration, and cost and latency engineering
- Strong written communication. You can explain technical decisions clearly to product, customer success, and customers themselves. We are level-agnostic on years; we care about what you have shipped
- Experience with Model Context Protocol (MCP) or agent orchestration tooling
- Curiosity about the Salesforce platform. You do not need to know it. We will teach you. But you should be excited about integrating agents with the system of record where most enterprise customer-facing work actually happens
- Experience with compound or agentic coding workflows (Claude Code, Cursor, or equivalent)
- Comfort in customer-facing technical contexts, including design partner work and customer demos (all virtual)
Benefits
- Bonus based on company and individual performance targets
- Medical, dental, and vision benefits
- Every other Friday off and a team that respects your time outside of work
- Flexible PTO
- 12 weeks paid family and medical leave, 16 weeks for birthing people
- Vacation bonuses
- Anniversary bonuses
- Company-paid life insurance
- 401(k) matching
- Cell phone reimbursement stipend
- Employee Assistance Program
Company Overview