First impressions matter. 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. TaskRay is the leader in post-sale work management in the Salesforce ecosystem. We help companies make the transition from sales to customer success frictionless, driving greater efficiencies and creating unmatched customer experiences – all within Salesforce.

Culture is at the heart of TaskRay. We look for team members who share our values and bring them to life in their own ways. If these resonate with you, TaskRay could be the place for you:

Connection. Cultivate authentic connections with customers, partners, and each other. We believe in a customer-first mindset across everything we do, continuously learning and focusing on the ‘We’ rather than the ‘I’.

Integrity. We are transparent, sharing information and feedback freely. We infuse every action with honesty, fairness, and respect for customers and colleagues alike. We do the right thing, even when no one is watching.

Hunger. We have high expectations and expect high performance of ourselves and our teams. We constantly look to innovate and improve, unleashing our creativity and persistence to find solutions and deliver exceptional results.

Thrive. We love what we do and bring our best selves to work every day. We show up as real human beings who speak from the heart, value others’ contributions and invest in each other’s growth.

The Role

We are hiring a Staff AI Engineer to lead the technical design of TaskRay's AI platform. This role sits at the center of our next 18 months: an off-platform agent layer that integrates deeply with our Salesforce-native distribution, productized through outcome-based packaging and validated through engagements with our design partner customers.

You will own the architecture, set the engineering standards for how we build with LLMs, and partner directly with our VP of Product & Engineering, our Architect, and our senior Salesforce engineering lead to ship. You will also be visible to customers: design partner work is how we learn what to productize, and you will be the technical voice in those rooms (virtually, not on-site).

We will sequence these agents deliberately, starting with internal-facing capabilities (the PM Agent and Execution Agent) before extending to the External Onboarding Agent. The MCP server is the foundation that underpins all three.

This is a builder's role with leverage. You will not be managing people on day one, but your technical judgment will shape what every other engineer on the team builds.

Note

We are hiring AI engineers, not Salesforce engineers. You bring the agent craft (production LLM systems, evals, retrieval, tool use, multi-step reasoning). We will teach you what you need to know about the Salesforce platform our product is built on. The integration work is real but it is not the center of the role; the agents are.

What You'll Do

Architecture and Technical Strategy

1. Own the architecture of TaskRay's off-platform AI tier, including the contracts that connect it to our Salesforce-native core
2. Make and defend build versus buy decisions across the agent stack: orchestration, retrieval, evaluation, observability, and guardrails
3. Partner with our Architect and senior Salesforce engineering lead on the data contract between the Salesforce platform and the off-platform AI layer
4. Translate the company's AI strategy into a buildable technical plan

Agent and AI Systems

1. Architect and lead the build of our MCP server, the platform layer that connects agents to TaskRay's project, customer, and onboarding data and gives us control over usage analytics, packaging, and external agent connections
2. Design and lead the build of our PM Agent, an internal-facing agent that materially increases customer team productivity by maintaining live project status and surfacing the next best action
3. Design and lead the build of our Execution Agent, an internal-facing agent that completes tasks on behalf of human counterparts inside TaskRay workflows
4. Design and lead the build of our External Onboarding Agent, the customer-facing agent that handles status updates, document collection, and end-customer interaction across the onboarding lifecycle
5. Build the eval, observability, and feedback infrastructure that lets us iterate on agents safely against real customer data
6. Set our approach to retrieval, tool use, and multi-step reasoning. We expect production-quality systems, not demo-quality

Design Partner Engagements

1. Partner with our design partner customers (3 to 5 in the first phase) to discover the repeatable workflow patterns worth productizing across the PM Agent, Execution Agent, and External Onboarding Agent
2. Lead the technical scoping for design partner work: what we build custom, what we build into the core product, what we deliberately do not build
3. Be the technical voice in those engagements alongside Product. Engagements run via video and shared tooling, not on-site

Engineering Leadership and Standards

1. Establish TaskRay's engineering standards for AI feature development: prompt iteration, eval-driven workflows, agent observability, cost and latency budgets, security and compliance posture
2. Actively contribute to our agentic coding standards and norms
3. Mentor senior and mid-level engineers contributing to AI work, and shape the broader hiring bar for AI capability on the team

What we're looking for:

1. Track record of shipping production agent systems at meaningful scale (real users, real reliability requirements, real failure modes you have debugged)
2. Deep, hands-on experience designing agent systems in production: tool use, multi-step reasoning, retrieval pipelines, and the evals required to iterate on them safely
3. Strong Python proficiency (the lingua franca of the AI stack), with production experience deploying real systems
4. Hands-on experience with Anthropic Claude or comparable LLM provider APIs at production scale, including reliability patterns, eval harnesses, and cost and latency engineering
5. Demonstrated technical leadership: scoping work for multiple engineers, making and defending architectural decisions, and partnering credibly with senior stakeholders. We are level-agnostic on years; we care about the work
6. Comfort in customer-facing technical discovery and design partner contexts. You can listen well, scope tightly, and hold your own with a senior buyer

Strongly Preferred

1. Experience with Model Context Protocol (MCP), agent orchestration frameworks, or comparable tooling
2. Experience operating in compound or agentic development workflows (Claude Code, Cursor, or equivalent), with a point of view on how teams should adopt them
3. Background that includes one or more of: customer-embedded technical engagements, ML platform, or research-to-production transitions

Compensation

Cash compensation for this role is commensurate with experience. The estimated salary range is between $163,000 - $246,000 per year. This position is also eligible for bonus based on company and individual performance targets.

Additionally, TaskRay offers highly competitive non-cash compensation including:

1. Medical, dental, and vision benefits
2. Every other Friday off and a team that respects your time outside of work
3. Flexible PTO
4. 12 weeks paid family and medical leave, 16 weeks for birthing people
5. Vacation bonuses
6. Anniversary bonuses
7. Company-paid life insurance
8. 401(k) matching
9. Cell phone reimbursement stipend
10. Employee Assistance Program

We value diversity, equity, and belonging

At TaskRay, we celebrate differences and believe diverse teams create better solutions and stronger connections. We’re committed to providing equal employment opportunities to all qualified applicants regardless of race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, pregnancy, genetic information, veteran status, or any other status protected by law. If you need accommodations during the application or interview process, please let us know. And if you meet most but not all of the qualifications, we encourage you to apply—we’d love to hear from you.

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