Forward Deployed Engineer | San Francisco | $300K + equity

Harrison Clarke; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

Harrison Clarke partners with a high-growth, venture-backed AI healthcare company using artificial intelligence to transform how healthcare organisations operate and deliver value. This is an opportunity to join a small, ambitious engineering organisation where technical talent has a direct impact on the product, customers and wider business.

We’re looking for a Forward Deployed Engineer to sit at the intersection of engineering, AI and customer delivery.

Qualifications

• At least 2 years of professional software engineering experience in shipping production software.
• Strong proficiency in Python or another modern language and solid fundamentals in software design, debugging, testing and system architecture.
• End-to-end ownership: experience taking projects from an ambiguous initial problem through implementation, deployment and ongoing iteration.
• Customer-facing technical ability: comfortable working directly with customers, asking the right questions, communicating trade-offs and translating business needs into engineering solutions.
• Practical AI experience: experience building with LLMs, AI APIs, agentic workflows or other AI-enabled applications like production deployments.
• Integration and systems experience: familiarity with APIs, databases, third-party systems and production infrastructure.

Responsibilities

• Own end-to-end customer deployments: understand requirements, design solutions, build and productionize.
• Build production-grade software: write high-quality code, develop integrations and deliver reliable apps.
• Translate ambiguity into execution: convert loosely defined problems into concrete technical tasks.
• Integrate AI into real-world workflows: deploy AI capabilities into customer environments.
• Solve complex technical problems: debug across APIs, data pipelines, and infrastructure.
• Drive customer outcomes: monitor performance, gather feedback, iterate for adoption.
• Shape the product: feed deployment insights back to engineering to build scalable capabilities.
• Operate with high ownership: work autonomously in a fast-moving environment.

Skills

Software engineering

Python

System design

Debugging

Production software

Customer-facing

Tools

APIs

Databases

Third-party systems

Production infrastructure

Job description

We’re partnering with a high-growth, venture-backed AI healthcare company using artificial intelligence to transform how healthcare organisations operate and deliver value.

Backed by leading investors, including Sequoia Capital, the company is building AI-native solutions to tackle complex, real-world challenges across healthcare. Having demonstrated significant commercial traction and rapid revenue growth, the business is now scaling its engineering team to meet increasing customer demand.

This is an opportunity to join a small, highly ambitious engineering organisation where technical talent has a direct impact on the product, customers and wider business.

The Role

We’re looking for a Forward Deployed Engineer to sit at the intersection of engineering, AI and customer delivery.

You’ll work directly with customers to understand complex operational challenges, translate ambiguous requirements into technical solutions, and build and deploy software that delivers measurable value in production.

This is a hands-on engineering role, not a traditional solutions engineering or implementation position. You’ll write code, design systems, integrate with existing infrastructure and work through the technical challenges that arise when deploying AI into real-world environments.

Responsibilities:

• Own end-to-end customer deployments: Take responsibility for understanding customer requirements, designing technical solutions, building them and getting them into production.


• Build production-grade software: Write high-quality code to solve complex customer problems, develop integrations and deliver reliable, scalable applications.


• Translate ambiguity into execution: Work directly with customers to identify pain points, understand existing workflows and turn loosely defined problems into practical technical solutions.


• Integrate AI into real-world workflows: Help deploy AI-powered capabilities into customer environments, navigating the challenges of integrating intelligent systems with existing software, data and operational processes.


• Solve complex technical problems: Debug issues across APIs, data pipelines, application logic and infrastructure, ensuring deployed solutions perform reliably in production.


• Drive customer outcomes: Monitor how solutions perform in practice, gather feedback and iterate quickly to improve adoption, reliability and measurable business impact.


• Shape the product: Feed insights from customer deployments back into the core engineering team, helping identify recurring problems and opportunities to build more scalable, reusable product capabilities.


• Operate with high ownership: Work autonomously in a fast-moving environment, balancing technical execution, customer priorities and commercial outcomes.

Qualifications:

• Strong software engineering experience: At least 2 years of professional software engineering experience, with a track record of building and shipping production software.


• Excellent coding ability: Strong proficiency in Python or another modern programming language, alongside solid fundamentals in software design, debugging, testing and system architecture.


• End-to-end ownership: Experience taking projects from an ambiguous initial problem through implementation, deployment and ongoing iteration.


• Customer-facing technical ability: Comfortable working directly with customers, asking the right questions, communicating technical trade-offs and translating business needs into engineering solutions.


• Practical AI experience: Experience building with LLMs, AI APIs, agentic workflows or other AI-enabled applications is valuable. We’re particularly interested in engineers who have moved beyond experimentation and delivered working solutions.


• Integration and systems experience: Familiarity with APIs, databases, third-party systems and production infrastructure, with the ability to work across the stack when required.

Why Join?

• Real-world impact: Build and deploy AI solutions addressing meaningful challenges in healthcare.


• High ownership: Take responsibility for technical delivery and see the direct results of your work.


• Strong commercial momentum: Join a well-funded business that has demonstrated substantial revenue growth and is investing in expanding its engineering organisation.


• Close-knit engineering team: Work alongside a small, talented team where individual contributions have significant influence.