• Ensono is building a new portfolio of Managed AI Services, and we need a Product Architect to design the technical foundation. This is a senior, hands-on role where you'll architect how our AI services are built, integrated, and delivered to enterprise clients. • You'll work at the intersection of cloud platforms, AI/ML technologies, and managed services operations—designing solutions that integrate third-party AI capabilities (Azure OpenAI, AWS Bedrock, etc.) into scalable, secure, enterprise-grade managed offerings. • This isn't about building AI models from scratch; it's about architecting the infrastructure, integrations, and operational frameworks that allow Ensono to deliver AI services reliably to clients. • This is not a client-facing role, but at times you'll engage with customers to understand their needs, translate those into technical architectures, and collaborate closely with Security, the CTO office, and Operations to ensure our services are production-ready.

• Design and curate upper-undergraduate and graduate-level Biology problems with clear, fully worked solutions. • Create challenging, realistic tasks that expose failure modes in frontier AI systems. • Convert diagram-heavy or multi-part biology questions into self-contained, text-only problems with definitive answers. • Write rigorous explanations and verify scientific accuracy throughout the problem and solution. • Evaluate AI-generated responses, diagnose errors, and refine questions to meet difficulty targets. • Review Biology tasks created by others and improve clarity, correctness, and realism. • Collaborate with cross-functional teams to maintain consistent standards across large task batches.

• Design and solve challenging Maths problems to probe the limitations of large language models. • Create clear, high-quality, step-by-step solutions with well-articulated reasoning. • Collaborate with LLM researchers to align problems with evaluation goals, especially in areas where models struggle (e.g., abstraction, multi-step reasoning, symbolic manipulation). • Help define new evaluation benchmarks based on Mathematics curricula spanning early undergraduate to PhD-level topics.

• Lead a team of AI Engineers, ensuring alignment on goals, quality and delivery timelines. • Mentor and coach team members to support their technical and professional growth. • Drive engineering excellence by promoting best practices in coding (PEP-8, Clean Code), Test-Driven Development, code review, CI/CD and responsible AI development. • Plan and manage team capacity, sprints and milestones to ensure predictable delivery. • Own the design, evolution and operation of our RAG and agentic AI services — retrieval, embedding, indexing, orchestration, evaluation and LLM Ops. • Set and maintain standards for prompt engineering, evaluation harnesses, guardrails, hallucination mitigation and content safety. • Partner with the Data team to expose curated Druid datasets through natural-language interfaces (text-to-SQL / semantic search) and ensure quality and consistency end-to-end. • Collaborate with Product, UX and Architecture to translate customer and internal use cases into well-defined AI capabilities with clear acceptance criteria. • Champion responsible AI — bias awareness, transparency, privacy, data minimisation, evaluation, monitoring, and clear in-product communication of model limitations. • Collaborate with other Team Leaders, Development Managers, Architects and Product Owners to align engineering execution with business objectives. • Contribute to the evolution of development processes, CI/CD pipelines and DevOps practices. • Foster a culture of continuous improvement, innovation and knowledge sharing — including a research-aware approach to a fast-moving field.