Senior Solution Architect

The Role We are looking for a Senior Solution Architect who is a genuine technical generalist: someone who reasons from first principles, is insatiably curious about how things work under the hood, and can move fluidly between low-level implementation detail and high-level business narrative. You will own the technical shape of diverse client engagements - from cloud and full-stack platforms to modern AI and inference systems - and remain hands-on through delivery rather than handing designs over the wall. This is a role for a builder-architect: equally comfortable whiteboarding a system with a principal engineer, debugging an inference bottleneck, or explaining a trade-off to a customer and internal teams in plain language. What You'll Do Own end-to-end solution architecture for client engagements across cloud, data, full-stack, and AI/ML workloads, balancing technical rigour with cost, security, and time-to-value. Design from first principles — decompose unfamiliar problems, evaluate options on their merits, and justify decisions rather than defaulting to patterns or hype. Stay hands-on through delivery: prototype, review code and infrastructure, unblock engineering teams, and ensure what was designed is what actually ships. Simplify complex technical concepts for business, leadership, and customer audiences — translate architecture into outcomes, risks, and options stakeholders can act on. Lead client conversations, discovery workshops, and solution presentations; act as a trusted technical advisor and the bridge between engineering and the business. Architect AI-centric solutions — reason about model selection, inference architecture, tuning/optimization, and the systems that serve models in production. Coach and uplift teams — mentor engineers and associate architects, run design reviews, and raise the technical bar through teaching, not gatekeeping. Explore and prototype emerging technologies, bringing a spirit of creative, spontaneous problem-solving to engagements where the right answer isn't yet obvious. Core Technical Competencies You should bring a strong working foundation across the following — breadth as a generalist, with the ability to go deep wherever a problem demands it: System design fundamentals — scalability, reliability, data modelling, consistency, latency, and the trade-offs between them. Cloud architecture and services — ideally AWS — including compute, storage, networking, serverless, and well-architected design principles. Full-stack development — backend and frontend, APIs, and the ability to read, write, and review production code with credibility. Software engineering best practices — version control, testing, design patterns, and maintainable, observable systems. DevOps and platform engineering — CI/CD, IaC, containerization, orchestration, and operational concerns across the delivery lifecycle. AI & Inference Systems A solid, current understanding of how modern AI systems are built and operated — not just how to call an API: Underlying architecture of AI systems and inference pipelines — how models are served, scaled, and integrated into broader applications. Model lifecycle fundamentals — how model development, fine-tuning, and optimization work, and when each is appropriate. Practical grasp of inference economics and performance — latency, throughput, cost, quantization, and the levers that move them. Familiarity with GenAI patterns — retrieval-augmented generation, agentic workflows, evaluation, and grounding/guardrails. Who You Are Beyond the skills, we're looking for a particular mindset: A first-principles thinker who questions assumptions and reasons up from fundamentals rather than relying on received wisdom. A curious generalist and technology enthusiast with a genuine drive to understand how things work under the hood. A creative, spontaneous problem-solver — comfortable improvising, prototyping, and finding non-obvious paths when the textbook answer falls short. A clear communicator who is well-spoken and equally effective with deeply technical engineers and non-technical executives. A natural teacher — someone who enjoys explaining, simplifying, and helping others level up. Strong attention to detail paired with the judgment to know when to zoom out to the bigger picture. Experience & Qualifications 6–8 years of professional experience, with a strong foundation as a software developer/engineer. Demonstrated progression into solution architecture — associate, and ideally senior-associate level, exposure. A track record of delivering technical solutions in client-facing or product environments. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Relevant cloud certifications (e.g., AWS Solutions Architect) are a strong plus. Nice to Have Prior consulting or professional-services delivery experience. Hands-on experience with Bedrock, SageMaker, or comparable ML/GenAI platforms. Experience presenting at workshops, enabling teams, or producing technical thought-leadership content.