Senior Backend Software Engineer

Holokai
Washington, District of Columbia, United StatesFull-timePosted Sep 16, 2026

About the role

Senior Backend Software Engineer

Function: Engineering

Location: Metro DC Preferred (Hybrid: Tuesdays & Thursdays In-Office)

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

Relational databases, PostgreSQL: schema design, query performance, migrations

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

Enterprise security, compliance, or governance experience (e.g. SOC 2, GDPR, etc.)

Compensation & Benefits

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.

How to Apply

Complete the LinkedIn process or send your resume and a brief note to talent@holokai.ai

Responsibilities

  • Build backend services: APIs, data pipelines, integrations, and core business logic
  • Develop policy enforcement engines and rules processing
  • Create multi-step AI plans using LLMs with policy checkpoints
  • Design PostgreSQL schema and optimize queries
  • Monitor, debug, and fix production issues

Qualifications

  • Strong production experience in TypeScript and Go
  • Experience designing and building APIs and backend service architecture
  • Proficient in relational databases, especially PostgreSQL
  • Familiarity with AI-assisted development tools
  • Production experience with AWS and containerized deployments

Benefits

  • Comprehensive Healthcare Coverage (including Vision, Dental, and Life)
  • Unlimited PTO
  • Hybrid flexibility
  • Opportunity for equity participation

Skills mentioned

TypeScriptGoPythonBackend DevelopmentREST APIsPostgreSQLQuery OptimizationAWSDockerDistributed Systems

About Holokai

Implementing AI across an organization can feel overwhelming—fragmented tools, security headaches, integration silos, and unpredictable outcomes. Holokai is purpose-built to tackle these obstacles head-on. Our platform fills the potholes and smooths the speed bumps of enterprise AI adoption, allowing organizations to rapidly capture value from AI and scale it reliably, effectively, and accessibly across the board.

Technology11-50 employees