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AI Product Engineer
Location:
US-CA-San Francisco
Jobcode:
e97adc4c-e77e-4c29-9faf-30dbfc01aeab
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AI Product Engineer

Applied AI / Product Engineering | San Francisco | Hybrid

About the Company

We are representing a high-growth applied AI company building production-grade software for large organizations operating in complex, highly regulated environments.

The company develops AI-powered platforms and tailored applications that modernize critical workflows across sectors including government, healthcare, insurance, and financial services. Its technology is designed for environments where security, reliability, data governance, and real-world deployment matter as much as model performance.

The engineering culture is highly hands-on and product-focused, with small teams working closely with customers to take ideas from ambiguous requirements through to production software.

The Role

This is an opportunity to join as an AI Product Engineer, owning the development of AI-enabled software from customer requirements through production deployment.

You will sit at the intersection of product, engineering, and applied AI: working directly with customers and internal stakeholders to understand complex workflows, define what should be built, and then write the software that brings those products to life.

The role is primarily hands-on engineering, with a backend-leaning full-stack focus. You will collaborate closely with AI/ML specialists while owning the application and product layer around model outputs.

This role is ideal for someone who enjoys zero-to-one development, is comfortable operating without a detailed playbook, and wants meaningful ownership over software used in demanding real-world environments.

What You'll Do

  • Build and deploy AI-powered software products end-to-end, from initial requirements through production.
  • Work directly with customers and stakeholders to understand complex operational workflows and translate them into effective product experiences.
  • Own full-stack product development with a strong backend emphasis.
  • Build primarily with TypeScript and Python, using React for frontend development where required.
  • Develop applications and workflows that integrate with AI and machine learning systems.
  • Partner closely with AI/ML engineers responsible for areas such as model selection, training, evaluation, and model performance.
  • Design and integrate APIs, microservices, databases, and cloud-based application infrastructure.
  • Take products from ambiguous early-stage requirements to usable, production-ready software.
  • Iterate quickly based on customer feedback and real-world usage.
  • Operate as a hands-on individual contributor while contributing to product decisions and technical direction.
  • Work across different customer problems and industry use cases as priorities evolve.
  • Participate in occasional customer-facing work while maintaining a strong focus on building and shipping software.

What We're Looking For

  • 2+ years of professional software engineering experience, with scope and seniority calibrated to experience.
  • Strong experience building and shipping production software as a hands-on engineer.
  • Evidence of having taken products, features, or systems from 0-to-1, particularly within startup or high-growth environments.
  • Strong proficiency in TypeScript or Python; experience with both is preferred.
  • Full-stack engineering capability with a backend-leaning skill set.
  • Experience working directly with customers, users, or business stakeholders to define requirements and determine what should be built.
  • Strong product judgment and the ability to turn ambiguous problems into practical software solutions.
  • Comfortable operating in fast-moving environments where priorities can evolve quickly.
  • A track record of meaningful technical or product impact.
  • Ability and willingness to remain highly hands-on with coding regardless of seniority.
  • Strong communication skills and confidence working across engineering, AI/ML, product, and customer-facing teams.

Nice to Have

  • Experience building products that incorporate AI or machine learning capabilities.
  • Familiarity with AI model workflows, evaluations, or production AI systems.
  • Experience with React(link removed)>
  • Experience designing or consuming RESTful APIs(link removed)>
  • Experience working with microservices architectures(link removed)>
  • Familiarity with major cloud platforms such as AWS, GCP, or Azure(link removed)>
  • Strong database and data-management fundamentals.
  • Experience in an early-stage startup, as a founding engineer, or building new products from scratch.
  • Exposure to regulated or operationally complex sectors such as healthcare, financial services, insurance, or the public sector.
  • Experience deploying software where security, compliance, or data governance are important considerations.

Why This Role Is Exciting

  • End-to-end ownership: You will have meaningful responsibility from initial customer problem through shipped production software.
  • Real product influence: Engineers are expected to help determine what gets built rather than simply execute predefined specifications.
  • Applied AI at production scale: Work on AI systems designed for practical deployment in complex, high-stakes environments.
  • High coding ownership: This remains a deeply hands-on engineering role, including at more senior levels.
  • Zero-to-one engineering: Solve new problems where the product, technical approach, and user experience are still being defined.
  • Close collaboration with AI specialists: Work alongside engineers focused on machine learning while owning the application layer that turns AI capabilities into usable products.
  • Impact-driven progression: The environment rewards engineers who take ownership, ship quickly, and create measurable product impact.

Work Model

  • Full-time position.
  • Hybrid in San Francisco(link removed)>
  • Three days per week in the office(link removed)>
  • Regular collaboration with engineering, AI/ML, and customer-facing teams.
  • Some customer interaction and occasional travel may be required.
  • Existing H-1B transfers can be supported.
  • Green card applications can be supported.
  • New H-1B sponsorship is not available.

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