Senior Backend Software Engineer
Summary
Build core backend services for Holokai's enterprise AI-governance platform — policy enforcement, LLM agentic orchestration, and a model-agnostic gateway — at an early-stage startup. Day-to-day is hands-on TypeScript and Go (some Python) with PostgreSQL and AWS, shipping and owning production code alongside the co-founders.
Type: Full-Time (must be currently authorized to work in the United States)
Reports To: VP of Engineering
About Holokai
Holokai is building the platform enterprises need in today’s dynamic AI landscape to accelerate the secure adoption of AI. Our product lets organizations deploy AI tools safely through model access controls, distributed governance, and real-time policy enforcement, while still delivering real user productivity through a desktop chat experience and integrated agentic workflows. We are an early-stage startup with pilot customers, rapid product iteration, and direct customer feedback loops.
The Role
We’re looking for a backend engineer to build core products alongside our co-founders and senior engineering team. You won’t pull pre-scoped tickets from a backlog. You’ll work with our senior engineers and leadership to decide what to build, then build it well.
The Holokai platform spans a user desktop application, policy enforcement engine, an agentic workflow orchestrator, a model-agnostic gateway, and a SaaS management console. You’ll work across all of it, primarily in TypeScript and Go with some Python. The hard parts are genuinely hard, including sub-100ms policy evaluation, multi-model orchestration, and enterprise-grade security. We want someone who stays clear-headed in that complexity.
We need engineers who have built and owned critical production solutions running at real scale to serve exacting enterprise customers. We’re heavy AI users in how we build, not just in what we ship. AI-assisted development is core to how this team works; we want someone who puts AI to work but catches it when it’s about to steer them wrong. Write simple code, ship often, and own what you put in production.
What You’ll Work On
- Backend services: APIs, data pipelines, integrations, and core business logic
- Policy enforcement: deterministic evaluation engines, rules processing, and classification
- Agentic orchestration: multi-step AI plans using LLM’s, executed as deterministic workflows with policy checkpoints built in
- Model gateway: routing and translation across LLM providers, token management, and request handling
- Data layer: PostgreSQL schema design, query optimization, and data modeling
- Production ownership: you monitor, debug, and fix what you ship
Who Thrives Here
- Engineers who write code every day and want to keep it that way
- People who use AI tools seriously and keep hunting for the next edge
- Self-starters who take a problem, find the approach, and deliver without being told how
- People drawn to the applied science of AI who want to make enterprise AI work for real
How We Work
At a start-up our size and stage, there's no living in a silo.Engineering, product, sales, and customer success all own success together. We work hard and support each other, and no amount of great code makes up for being difficult to work with. We need curious people who have played the tech start-up game long enough to learn humility, drive and the genuine joy of working and succeeding on a great team.
Required Skills
- Strong production experience in TypeScript and Go (Python a plus): real services running in production, not scripts and notebooks
- Designing and building APIs (REST, gRPC, or similar) and backend service architecture
- Reading and extending code you didn’t write, quickly and confidently
- Fluent with AI-assisted development tools (Claude Code, Cursor, or similar); you use them daily and they make you meaningfully faster
- Production experience with AWS
- Containerized deployments (Docker, ECS, EKS, or similar)
- Self-directed and comfortable with minimal structure in a fast-moving start-up environment
Nice to Have
- LLM APIs and AI/ML pipelines: prompt engineering, model integration, token economics
- Policy engines or rules-based systems (OPA/Rego, decision engines, or similar)
- Message queues and event-driven architectures (RabbitMQ, SQS, Kafka)
- Frontend chops (React); not the focus, but handy for closing the loop on a feature
Compensation commensurate with experience, with the opportunity for equity participation. We offer comprehensive Healthcare Coverage (including Vision, Dental, and Life), Unlimited PTO, Hybrid flexibility, and more.
Education
Bachelor’s in Computer Science, Engineering, or a related field, or equivalent professional experience.