Solution Architect

We're the AI engineering partner enterprises bring in when the work has to be right the first time: regulated data, production load, and systems that have been running for a decade before we arrive. You'll ship to production in weeks rather than quarters, own what you build end to end, and work beside a senior team that has already done it at that scale.

We're looking for an architect who still builds. This isn't a role where you produce a diagram and hand it to a delivery team. You sit in the first client conversation, shape the solution, write the parts that set the pattern, and stay with it until it's in production. If your best work happens in a slide deck rather than a repository, this isn't the fit.

The job lives where the technical and the commercial meet. You'll translate a business problem into a system, an architecture into an estimate a client can approve, and a constraint into a tradeoff everyone actually understands. That means being credible in a room with a CTO and equally credible in a code review the same afternoon.

You'll own the shape of a solution from the first call. That starts with discovery: understanding what the client's business actually needs, what their existing systems and data can support, and where the real risk sits. It ends with a proposed architecture, a delivery plan, and an estimate you're willing to stand behind. You'll write the proposals and the technical documentation, and you'll present both to the people paying for them.

Once delivery starts you stay in it: setting up the foundations, making the decisions that are expensive to reverse, reviewing the work as it lands, and unblocking the team when reality disagrees with the plan. You'll also be the technical counterpart the client escalates to when something is wrong, and the one who tells them honestly when a scope change means a date moves.

Across engagements you'll help raise the bar: establishing the patterns our teams reuse, pushing back on architecture that's fashionable but unwarranted, and mentoring engineers into the judgment this role runs on. You'll also help scope new work as it comes in, including deciding when we're not the right partner for it.

• Have designed and delivered systems you personally stayed accountable for after launch, not just designed them.
• Still write and review code, and want to keep doing so.
• Can scope and estimate honestly, including saying a number a client won't like.
• Think in tradeoffs rather than best practices, and can explain a decision to a CTO and to a junior engineer in the same day.
• Have opinions about when NOT to use microservices, event sourcing, Kubernetes, or an LLM.
• Are comfortable being the technical face of an engagement, including in the difficult conversations.
• Write clearly: the architecture that survives is the one someone else can read six months later.
• Work well with legacy: most systems worth improving already exist and can't be stopped.
• Handle ambiguity as the default state of a new engagement, and know which questions collapse it fastest.
• Give and take direct feedback without it becoming personal.
• Deep experience across the stack, in Type Script and Node, Python, or both, with real production scars.
• System design at scale: data modelling, service boundaries, consistency, caching, queues, and failure isolation.
• Cloud architecture on AWS or GCP: networking, IAM, cost modelling, and choosing managed over self-run.
• Data architecture across relational, document, and vector stores, plus the pipelines that feed them.
• Integration work: third-party APIs, legacy systems, event-driven patterns, and migrations that run live.
• Security and compliance instincts: auth, tenancy, data residency, and what GDPR or SOC 2 changes about a design.
• A working grasp of AI system architecture: agents, RAG, evaluation, and the cost and latency envelopes they impose.
• CI/CD, infrastructure as code, observability, and the operational reality of running what you designed.
• Estimation and delivery planning: breaking a system into phases that ship value before they ship completely.

Our work spans AI products, fintech, healthcare, logistics, and B2B SaaS, usually as the engineering partner a company brings in when the stakes are high and the timeline is short. Engagements range from a greenfield platform where you set every decision, to threading AI capability through a system that's been running for a decade, where…