AI Product Engineer

Job Description Roles & Responsibilities Design and build end-to-end AI-powered product features, including assistants, copilots, knowledge tools, and automation workflows. Develop RAG pipelines covering document ingestion, vector search, embedding models, reranking, and retrieval quality evaluation. Build and integrate agent-based AI workflows capable of multi-step reasoning, tool use, and planning. Create user-facing interfaces using React, including conversational UIs, streaming responses, real-time feedback, and error handling. Design and build backend services and APIs in Python or Java to expose AI capabilities to products and platforms. Work with PostgreSQL to support AI product features, evaluation pipelines, and operational analytics. Define evaluation frameworks, quality metrics, and monitoring approaches to measure AI behaviour and detect regressions. Translate ambiguous product and operational requirements into well-scoped engineering problems with measurable outcomes. Build reusable components, API patterns, and AI integration libraries that enable scalable adoption across multiple entities. Desired Candidate Profile 5+ years of software engineering experience, with a strong track record of building and shipping production systems. Proven ability to own product features end-to-end across AI backend, API layer, and user interface. Strong Python experience, ideally building LLM-powered systems, AI pipelines, and backend services. Solid React experience, including component architecture, state management, performance optimisation, and responsive UI development Experience building production-grade backend APIs using Python or Java, with strong understanding of reliability, authentication, error handling, and scalability, Working proficiency with PostgreSQL, including schema design, query optimisation, and data modelling. Strong understanding of the practical challenges of deploying LLMs in production, including hallucination, latency, context degradation, and calibration. Experience with RAG systems, agentic AI workflows, LLM evaluation, or AI product monitoring is highly desirable. Exposure to tools and frameworks such as LangChain, LangGraph, vector databases, Docker, cloud platforms, and CI/CD pipelines would be advantageous. Strong product mindset, clear communication skills, and the ability to make evidence-based technical decisions. Company Industry ConsultingManagement ConsultingAdvisory Services Department / Functional Area IT Software Keywords AI Product Engineer Get real-time job updates only on our App