Full Stack AI Engineer
About The Position
We're looking for a Full Stack AI Engineer to own complete AI-native systems from concept through production at a fast-moving enterprise AI platform. This means product thinking, UX, frontend, backend, AI workflows, infrastructure, deployment, and iteration — all of it, not a slice of it. This is not a narrow frontend, backend, or machine learning role. You will take loosely defined business problems, design the user experience, decide how the system should work, build every layer, deploy it securely, measure whether it works, and improve it based on real usage. The hardest thing to find for this role is not technical skill — it is systems thinking. If you think beyond individual tickets, consider second-order effects before making technical decisions, and prefer ownership and ambiguity over narrowly scoped work, this role is a strong fit.
Requirements
- 5 or more years of professional software engineering experience with a track record of building and shipping real production systems, ideally from zero to meaningful scale
- Strong frontend experience with React, Next.js, and TypeScript
- Strong backend experience with Python, TypeScript, Node.js, or similar technologies
- Hands-on experience building production AI or LLM features, not just prototypes or API wrappers
- Deep understanding of RAG, agents, tool use, memory systems, context management, and evaluation frameworks
- Experience designing APIs, databases, data models, queues, event-driven systems, and distributed workflows
- Strong product judgment and enough design taste to turn complicated workflows into interfaces that feel obvious
- Strong understanding of authentication, permissions, encryption, secrets, data privacy, and secure software design
- High ownership — you do not wait for someone else to define every requirement, catch every edge case, or clean up after launch
- Clear written and verbal communication in an async, distributed environment
Nice To Haves
- Experience with PostgreSQL, Redis, vector databases, and search systems
- Familiarity with OAuth, SSO, SAML, SCIM, RBAC, audit logs, and enterprise integrations
- Experience with Docker, Kubernetes, and infrastructure as code
- Background deploying inside customer VPCs or private networking environments
- Experience with Figma or the ability to independently create strong product flows and interfaces
- Prior experience as a founding engineer or primary engineer at an early-stage company
Responsibilities
- End-to-End Product and System Ownership
- Build complete AI-native products from concept through production
- Turn loosely defined business problems into clear product and technical systems
- Design polished, simple interfaces for complex enterprise workflows
- Zoom in to debug a broken API call and zoom out to question whether the entire workflow is designed correctly
- Make architecture decisions based on scale, reliability, security, speed, and long-term maintainability
- Frontend and Backend Development
- Build responsive frontend applications and reusable component systems using React and Next.js
- Build secure APIs, backend services, data pipelines, databases, and asynchronous workflows
- Design systems for multi-tenancy, role-based access, auditability, data isolation, and enterprise security
- Connect the platform to enterprise systems including HRIS, ATS, CRM, email, calendars, and internal databases
- AI and LLM Engineering
- Develop LLM-powered features, agents, retrieval systems, evaluation pipelines, and decision workflows
- Build production AI systems with strong understanding of RAG, embeddings, tool calling, structured outputs, agent workflows, prompt design, model evaluation, and failure handling
- Design systems that operate inside customer VPCs, private clouds, and controlled enterprise environments
- Use AI coding tools aggressively to move faster without allowing generated code to reduce quality or understanding
- Infrastructure and Observability
- Deploy, monitor, and maintain cloud-based applications across GCP, AWS, Azure, and customer VPC environments
- Build observability, testing, logging, alerting, and evaluation systems so issues are caught before customers notice
- Design for CI/CD, infrastructure as code, and secure deployment pipelines
- Own authentication, permissions, encryption, secrets management, and data privacy across the stack
Benefits
- Paid Time Off in accordance with company policy
- Observance of Holidays per company guidelines
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
