Responsibilities
- Partner with stakeholders across the organization to identify and prioritize high-value opportunities for AI and automation.
- Design, develop, and support AI & automation systems that drive measurable business outcomes—from initial scoping to production deployment.
- Design, build, and maintain scalable infrastructure, including frontend interfaces, backend services, and the underlying AI platform layer.
- Create data pipelines and AI model context protocols, leveraging tools like MCP, LangChain, vector databases, and semantic search.
- Ensure the high availability, performance, and security of AI platform services.
- Contribute to platform growth by authoring SDKs, APIs, and comprehensive developer documentation.
- Translate complex AI concepts for non-technical stakeholders and keep business goals front and center.
- Keep pace with rapidly evolving AI models, frameworks, and research—and bring that knowledge back to the team.
Requirements
- Bachelor’s degree in Computer Science, Data Science, or a related field—or equivalent demonstrated experience through portfolio work, open-source contributions, or professional practice.
- Minimum of 3–5 years of experience in Software Engineering, Data Engineering, or Data Science, with meaningful hands-on experience building and deploying AI or LLM-powered systems.
- Proven experience moving AI models out of notebooks and into live, scalable, monitored production systems.
- Fluency in the full generative AI stack—LLMs, embeddings, vector databases, semantic search—and know how to apply them to real business problems.
- Strong SQL skills, experience with data warehousing, and you build clean, reliable pipelines that others can depend on.
- Write production-ready code. OOP, clean architecture, testable systems—these aren’t buzzwords to you, they’re defaults.
- Worked with automation tools (Zapier, Gumloop, n8n, or similar) and know when to reach for them versus when to build something custom.
- Connect technical decisions to business outcomes. You can hold the big picture and the implementation detail at the same time.
- As comfortable in a stakeholder meeting as you are in a code review.
- Believe in responsible, transparent AI practices and bring that lens to everything you build.
- Thrive in a remote-first environment, are self-directed, and genuinely enjoy collaborating across functions. Curiosity is your default setting.
- Can work a full-time W2 position on core U.S. business hours in your time zone.
- Ability to fulfill the job requirements with or without reasonable accommodations.
- Must be located in the United States and be legally eligible to work for us.
- Travel is required for an all-company meeting, and may be required once or twice per year for team or project meetings.
- Occasional after-hours/on-call for emergency support and special events (generally less than four times per year).
Nice to Have
- Built end-to-end systems with React/TypeScript/Next.js frontends and Python/FastAPI or Node.js backends—and you’re comfortable managing data with Postgres or Redis.
- Solid grounding in statistics, probability, and experimental design. You know how to evaluate model performance rigorously, design meaningful tests, and distinguish signal from noise.
Benefits
- Work from home with a company-provided MacBook and internet stipend.
- 21 days of flexible PTO + your birthday + holidays (with flexible substitution).
- Comprehensive medical, dental, and vision group health insurance, flexible spending accounts, and more.
- 401k match, professional development budget, robust wellness programs, pet insurance and many more perks and benefits.
Work Arrangement
Remote (Worldwide)
Team
Structure: dynamic team
Additional Information
- Must be located in the United States and be legally eligible to work for us.
- Travel is required for an all-company meeting, and may be required once or twice per year for team or project meetings.
- Occasional after-hours/on-call for emergency support and special events (generally less than four times per year).
- We prefer an excited candidate with a great attitude and less experience to an unmotivated or unengaged candidate with tons of experience.
