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You’ll own delivery end to end, from discovery and rapid prototyping through production rollout, adoption, and handover.\n\nJob Responsibilities:\nDiscover and shape: Embed with business teams, understand their workflows and pain points, and turn ambiguous needs into prioritised use cases with measurable success criteria.\nPrototype and iterate: Build working prototypes quickly, validate with users, and take viable solutions to production.\nBuild agentic workflows: Design reliable AI agents and workflows using LangGraph, LangChain, n8n, or similar, combining deterministic logic, LLM reasoning, tool calling, and human approvals.\nDevelop applications and backends: Build APIs, integrations, and lightweight UIs using Python, FastAPI, and PostgreSQL, including data ingestion and retrieval pipelines (search and vector services).\nEnsure quality and safety: Define evaluations, implement tracing and monitoring, and apply secure, responsible AI practices (least privilege, prompt-injection defences, auditability, human oversight) in line with government policies.\nDrive adoption: Own testing, rollout, documentation, user enablement,and support. Feed learnings back into reusable patterns and the core platform.\n\nJob Requirements:\n5+ years of software engineering experience, with ownership of production applications from ambiguous requirements through to deployment and support\nStrong Python (or another modern backend language), API design, async processing, and system architecture\nStrong PostgreSQL/relational database skills, plus practical knowledge of data pipelines, search, and vector retrieval\nHands-on experience with LLM applications, RAG, tool-calling agents, or workflow automation (LangGraph, LangChain, LlamaIndex, n8n, or equivalent)\nCloud-native deployment experience; AWS (Bedrock, OpenSearch) preferred, Azure or GCP acceptable\nExcellent communication and facilitation skills, with the ability to work with non-technical users and drive adoption\nComfortable with ambiguity and quick to learn new business domains\nNice to Have:\nConsulting, solutions engineering, or other user-facing, end-to-end delivery experience\nVisual workflow builder experience (n8n, Flowise), including custom nodes and integrations\nLLM evaluation, observability, or red-teaming experience\nExperience in regulated environments (data privacy, cybersecurity, government requirements such as IM8)\nSkills\nRequirements Management, AI Agents, Adaptive Reuse, Technical Writing, Public Policy, AWS, Identifying New Business Opportunities, Documentation, Automation Tools, Needs Analysis, implement production, Adoption, Python, Relational Databases, GCP, web-based 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