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Build automated tests and evaluation datasets for functional and non-functional behavior.\n· Diagnose model, retrieval, tool-use and integration failures.\n· Contribute to secure coding, documentation, peer review and release activities.\n· Participate actively in agile ceremonies, demonstrations and backlog refinement.\nWhat we need from you\n· 3+ years in software, data or AI engineering.\n· Strong Python or comparable programming skills, API development and version control.\n· Practical experience with LLM applications, RAG, agents, embeddings and structured outputs.\n· Ability to work iteratively with product, architecture, data and user-experience specialists.\nRelevant AI technologies and tooling\n· Hands-on experience building agents with at least one production-oriented framework such as LangChain and LangGraph, Microsoft Agent Framework or Semantic Kernel, OpenAI Agents SDK, AutoGen, CrewAI, or equivalent.\n· Strong Python skills and practical experience with FastAPI or similar API frameworks, Pydantic or comparable schema validation, asynchronous programming, Git and automated testing.\n· Practical experience implementing tool calling, structured outputs, agent state and memory, hand-offs, guardrails, retries, human-in-the-loop steps and deterministic workflow nodes.\n· Experience implementing RAG pipelines using embeddings, vector or hybrid search, metadata filters, reranking and evaluation datasets.\n· Familiarity with MCP, enterprise API integration, queues or events, containerization with Docker and deployment to Kubernetes or managed application platforms.\n· Ability to instrument agent executions using tracing and evaluation tools such as LangSmith, MLflow, Langfuse, OpenTelemetry or platform-native equivalents.\nMeasures of success\n· Working features delivered per iteration\n· Evaluation results and defect rates\n· Integration reliability\n· Code review and documentation quality\n· Contribution to reusable engineering assets\nKey interfaces\n· Other members of the AI Transformation & Agentic Systems Practice\n· PwC sector, functional, cloud, cyber, risk, Responsible AI and change specialists\n· Client business owners, product owners, technology teams and operational users\n· Technology alliance and implementation partners where relevant\nContribution to the practice\n· Support proposals, client workshops and market development appropriate to seniority.\n· Contribute reusable methods, patterns, code, assets and lessons learned.\n· Coach colleagues and participate in the capability’s continuous learning agenda.\n· Uphold PwC quality, independence, confidentiality and risk-management requirements.\n#LI-BS1 #LI-Hybrid","description_format":"text","description_chars":3022,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous 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