Principal Architect - AI-first IP Intelligence Platform

At S&W, we help our clients thrive by simplifying the complex, illuminating new paths, and shaping solutions that make a difference. As one of the UK’s top 10 fastest-growing accountancy firms, we have been a trusted partner since 1881—helping businesses and individuals meet challenges and seize opportunities across generations. Built on expertise and driven by ambition, we provide a comprehensive range of services, including tax and accountancy, advisory and assurance, corporate finance, and restructuring. We are defined by our purpose—to help navigate challenges, unlock potential, and achieve the extraordinary. S&W acquired ClearViewIP in September 2025 to complement the existing advisory services that S&W currently offers its clients including corporate finance, valuations, transaction services and forensic services, along with business tax, audit, consulting and business outsourcing services. The ClearViewIP team comprises experienced IP professionals, with decades of experience in managing, protecting and commercialising innovation and ensuring best practice IP approaches are deployed to help clients win in the market. Principal Architect – AI-First IP Intelligence Platform We are transforming a global IP intelligence organization from expert-driven workflows into an AI-first, scalable platform architecture. Our mission is to convert complex, knowledge-intensive IP workflows-prior art search, patent landscape analysis, FTO, competitive intelligence-into modular, explainable, enterprise-grade AI systems. Location: Gurugram, India Working format: 5 days per week in the office The Role You will work closely with the Director and Head of the Workbench Program in the UK, and partner with the India operations team to understand how the work is done today and translate that into the platform. This is an architecture role with long-term platform ownership and significant technical influence. It is not about maintaining existing systems. The foundations are being laid now, and you will be shaping them hands-on: AI-native workflows that reason over long technical documents and cite evidence Backend services that orchestrate large analytical workloads across a data platform, and the APIs around them. Modern frontend experiences built for reviewing output at scale (React/NodeJS or equivalent) - a near-term critical path for this hire Secure, enterprise-grade Azure-based deployments, with Databricks as the current leading platform for the data/AI layer. Robust DevOps and MLOps foundations, including model evaluation You will operate at both strategic and hands-on levels-designing long-term architectural blueprints while actively shaping core systems in their earliest stages. This role is not about maintaining existing systems. It is about laying the foundations for a platform that will define the next decade of the company’s growth. Technical Strengths 12-15+ years in software engineering, with significant architectural ownership Experience building large-scale, distributed, enterprise-grade systems Proven, hands-on track record designing and building modern backend AND frontend architectures - frontend/UI depth is essential, not a nice-to-have, for this role Strong experience in Azure cloud deployments; hands-on Databricks experience (PySpark, Delta Lake, MLflow) strongly preferred Technical Depth Polyglot capability (Python, TypeScript, Java, Go, Node.js or similar) Data storage and query design: SQL, Delta / Lakehouse patterns, search indexes Structured extraction from long documents; structured-output contracts with LLMs Batch inference at scale, and the failure modes of long-context model calls Infrastructure-as-code and CI/CD pipeline design APIs and service design Desirable: vector databases, semantic search, RAG architectures - though our work leans more on verified structured extraction than on retrieval alone Vector databases, Semantic search systems, RAG architectures, Knowledge graphs ​​​​​​​ Domain Advantage (Preferred) Experience in IP analytics, patent intelligence, legal tech, or other knowledge-intensive domains Exposure to patent data formats, citation networks, IPC/CPC classifications Experience building explainable systems in regulated or high-trust environments