Careers
Build AI that runs in the real world.
We are a small, engineering-first team building production AI systems for enterprise clients. We don't do demos. We don't build MVPs that can't scale. Every system we ship runs in a real business environment and solves a real problem.
Remote-first
Work from anywhere
Engineering culture
No sales-driven decisions
Real production work
Not demos or POCs
Direct client access
No intermediaries
Open Roles
Current openings
AI Engineer
You will design, build, and deploy AI agents and LLM-powered systems for enterprise clients. This means writing production-quality Python, architecting multi-agent pipelines, evaluating model performance, and owning systems end-to-end from scoping through post-deployment monitoring.
What we need
- 3+ years experience building ML or AI systems in production
- Strong Python skills FastAPI, async patterns, clean architecture
- Hands-on experience with LLM APIs (OpenAI, Anthropic, open-source models)
- Experience with vector databases, embeddings, and RAG pipelines
- Comfort working directly with clients and explaining technical decisions clearly
Nice to have
- Experience with LangChain, LangGraph, or similar agent frameworks
- Background in financial services, real estate, or other regulated industries
- Experience fine-tuning models (LoRA, QLoRA, RLHF)
AI Solutions Architect
You will lead technical scoping, system design, and architecture decisions for complex AI engagements. You will work closely with clients to understand their problems, define what we build, and ensure the systems we ship meet production requirements. You are the bridge between business outcomes and engineering execution.
What we need
- 5+ years in software engineering or AI/ML, with 2+ years in architecture or tech lead roles
- Deep understanding of AI system design agents, RAG, fine-tuning, MLOps
- Experience translating business requirements into technical specifications
- Strong communication skills you can explain architecture to both engineers and executives
- Proven track record delivering production AI systems
Nice to have
- Experience consulting for enterprise clients
- Domain knowledge in financial services or operations-heavy industries
- Familiarity with cloud infrastructure on AWS, GCP, or Azure
Full-Stack Engineer
You will build the interfaces, APIs, and integrations that bring our AI systems to life for client users dashboards, agent interfaces, admin panels, and data pipelines. You care about clean code, good UX, and systems that work reliably at scale.
What we need
- 3+ years of full-stack development experience
- Strong React/Next.js skills with TypeScript
- Solid backend experience Python or Node.js, REST APIs, PostgreSQL
- Experience integrating AI APIs and streaming responses into UIs
- Attention to detail on UX you notice when something feels off
Nice to have
- Experience with real-time systems (WebSockets, SSE)
- Background working on B2B SaaS products
- Familiarity with deployment on Vercel, AWS, or GCP
Java Backend Engineer
You will build and maintain robust backend services and integrations for enterprise clients particularly where Java is the dominant language in their stack. This includes integrating AI systems with existing banking cores, ERPs, and legacy enterprise platforms.
What we need
- 4+ years of Java backend development
- Strong Spring Boot experience REST APIs, microservices, security
- Experience integrating with enterprise systems (banking cores, ERP, CRM)
- Solid understanding of system design and distributed systems
- Ability to read and understand existing codebases quickly
Nice to have
- Experience in financial services or insurance technology
- Familiarity with AI/ML system integration
- Knowledge of Kafka, RabbitMQ, or similar messaging systems
MLOps Engineer
You will own the infrastructure layer that keeps our AI systems reliable in production model serving, monitoring, retraining pipelines, and deployment automation. You believe that the work doesn't end at launch and take pride in systems that perform consistently over time.
What we need
- 3+ years in DevOps, platform engineering, or MLOps
- Experience with model serving infrastructure vLLM, BentoML, Triton, or similar
- Strong Kubernetes and Docker skills
- Experience with monitoring and observability Prometheus, Grafana, or similar
- Python scripting and automation skills
Nice to have
- Experience with LangFuse, Weights & Biases, or similar LLM observability tools
- Background with CI/CD pipelines for ML systems
- Cloud certifications (AWS, GCP, or Azure)
Apply Now
Think you're a good fit?
Fill in the form below. We read every application. If there's a fit, we'll reach out within a week for a first conversation.