Full Stack AI Engineer

**Location: Remote \| Type: Contract** **About Newpage Solutions** Newpage Solutions is a global digital health innovation company helping people live longer, healthier lives. We partner with life sciences organisations which include, pharmaceutical, biotech and healthcare leaders, to build transformative AI and data driven technologies addressing real\-world health challenges. From strategy and research to UX design and agile development, we deliver and validate impactful solutions using lean, human\-centered practices. We are proud to be a ‘Great Place to Work®’ certified company for the last three consecutive years. We also hold a top Glassdoor rating and are named among the "Top 50 Most Promising Healthcare Solution Providers" by CIOReview. As an organisation, we foster creativity, continuous learning and inclusivity, creating an environment where bold ideas thrive and make a measurable difference in people’s lives. **Your Mission** We are hiring Fullstack AI Engineers to build the systems that make AI products work in production. You will wire models, retrieval, tools, and data into something users can actually rely on—and you will own the backend, the integration surface, and the infrastructure underneath. You will also stand up prototype front\-ends to make ideas tangible quickly, even though a front\-end specialist will own the polished surfaces. You treat AI as the substrate of how software gets built—not a tool to be cautious of, not something you are "exploring," but the medium you work in. You live at the current edge of AI development and work fluently in modern Python, comfortable enough in TypeScript to move across the stack, and at home with Claude Code, Cursor, agents, eval harnesses, and MCP as part of the daily toolkit. This is a builder\-first individual\-contributor role. You will not wait for a refined backlog, a PM in the middle, or a separate platform team. You will pick up an AI capability, build it end\-to\-end, and stand it up in production yourself. **What You’ll Do** **Build with AI** * Build and ship the AI engine: retrieval\-augmented generation, context\-aware reasoning, evidence citation, and the evaluation harness around it. * Architect production\-grade agentic applications using LangGraph, AutoGen, Claude Agent SDK, OpenAI Assistants, or your own orchestration layer. * Integrate frontier and self\-hosted LLMs (Claude, GPT, Gemini, open\-weight models) with tools, data, and external systems through MCP and custom connectors. * Apply RAG techniques where they actually help: vector databases (Pinecone, Chroma, Weaviate, pgvector), hybrid retrieval with ElasticSearch or Solr, BM25 \+ similarity search, re\-ranking. * Maintain vendor\-agnostic LLM abstractions so providers can be swapped behind a clean interface as enterprise constraints evolve. * Design prompt and context engineering frameworks that optimize accuracy, repeatability, cost, and latency. **Build the backend a