Senior work.
No overhead.
We are a small, expert team building leading-edge Azure, AI, and data work. No big-firm overhead, no junior handoffs, AI tooling throughout.
What working here looks like.
Expert engineers, AI-paired
Every engagement is owned end-to-end by senior engineers who use AI tooling throughout: Copilot, Claude, automated review. You spend your time on the hard parts, not scaffolding and boilerplate. Faster for the client, more interesting for you.
Leading-edge technology
Azure, Microsoft Fabric, Azure OpenAI, Synapse, Power Platform, .NET. We work with the technologies that are actually moving. No decade-old legacy codebase that nobody wants to touch; every engagement uses the current platform.
No big-firm overhead
Small team. Direct client relationships. Fast decisions. No pre-sales handoff to a delivery team that was never in the room, no approval chain before a client gets a real answer. What you hear on day one is what you are actually building.
National client base
We work with clients across the United States: Healthcare, Financial Services, Energy, Manufacturing, Retail, and more. Varied domains mean you are learning constantly, not spending your career on one industry's edge cases.
Work that fits the problem
Advisory retainers, fixed-scope builds, embedded augmentation. Some engagements are six-week sprints; others are multi-quarter programs. We hire people who read the situation and adapt the approach, not those who prefer to repeat the same playbook.
Outcome-focused culture
The measure is what changes in the client's business: cost reduced, decision cycle shortened, legacy system retired. We track that and talk about it. Hours logged and slides produced are not metrics here, and the clients we work with are not buying activity.
The kind of engineers we hire.
Deep in at least one area
Azure infrastructure, data engineering, Power BI, Azure OpenAI, .NET development. Senior means you have real scars from shipping something hard in production.
Broad enough to collaborate
On a small team, everyone touches adjacent problems. You do not need to be an expert in everything, but you need to be able to have an informed conversation about it.
Comfortable with ambiguity
Consulting work rarely arrives with a clean spec. You need to be able to scope the problem, ask the right questions, and start before everything is answered.
Current openings.
Developer
Here's a single paragraph for a Full Time Full Stack Developer: We're hiring a Full Time Full Stack Developer to build and maintain end to end web applications across the frontend, backend, and data layers. You'll design intuitive, responsive user interfaces, implement robust APIs and services, and shape the underlying data models and infrastructure that bring it all together, partnering with product managers, designers, and fellow engineers to ship features that are fast, reliable, and a pleasure to use. The ideal candidate has 3+ years of professional software development experience with a strong portfolio of shipped web products, is fluent in modern JavaScript or TypeScript along with a frontend framework such as React, Vue, or Angular, and is equally comfortable on the server side with Node.js, Python, Go, or a similar stack. You should have solid experience with relational and NoSQL databases, RESTful and/or GraphQL API design, version control with Git, and cloud platforms such as AWS, GCP, or Azure, plus a working understanding of CI/CD, testing, and observability. Just as important, you bring strong fundamentals in data structures, system design, and clean code, a pragmatic approach to tradeoffs between speed and quality, and clear communication skills that let you collaborate effectively with both technical and non technical stakeholders while mentoring teammates and contributing to a healthy engineering culture.
Apply →Senior AI Developer
We're looking for a Senior AI Developer to design, build, and deploy production grade machine learning and generative AI systems that solve real business problems. You'll own the full lifecycle of AI features, from framing the problem and selecting the right modeling approach, through training, fine tuning, or prompt engineering, all the way to deployment, monitoring, and iteration, working closely with product managers, data engineers, and software engineers to translate ambiguous requirements into reliable, scalable systems. The ideal candidate has 8+ years of software engineering experience with at least 5 years focused on machine learning, deep learning, or applied AI, is fluent in Python and modern ML frameworks such as PyTorch or TensorFlow, comfortable with cloud platforms, and experienced with the tooling around large language models, including vector databases, RAG pipelines, agent frameworks, and evaluation harnesses. Just as important, you bring sound judgment about when to use AI and when not to, a pragmatic eye for cost, latency, and quality tradeoffs, and clear communication skills that let you partner effectively with both technical and non-technical stakeholders, while mentoring more junior engineers on best practices in MLOps, evaluation, and responsible AI.
Apply →Start your next chapter.
Senior work on hard problems, without the big-firm overhead. If that is what you are looking for, we want to hear from you.