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      AI Engineer: Agentic AI & Full Stack AI Solution

      Advisory

      Location: Lahore
      Job Responsibilities
      • Design, build and deploy agentic AI solutions: agents that can reason, plan, use tools, keep memory and run multi step workflows, built on LLMs and frameworks such as LangChain and LangGraph, or on workflow platforms like n8n, Dify or Power Automate;
      • Connect agents to the enterprise by building and integrating MCP (Model Context Protocol) servers and tools, so they can work securely with applications, APIs, databases and business systems;
      • Develop AI powered backend services and APIs using Python and FastAPI or equivalent frameworks;
      • RAG is a core part of the job: document ingestion, chunking, embeddings, vector search, retrieval and reranking, and wiring all of this into databases, data lakes, warehouses and other enterprise data platforms;
      • Deploy and run AI applications  using the right compute, storage, networking, security and AI services, and make sure they follow the global security and compliance standards and best practices;
      • Implement authentication, authorization, secrets management, logging, monitoring, and responsible AI practices;
      • Work closely with data scientists, data engineers, software engineers, and business stakeholders to translate client requirements into AI solutions that hold up in production;
      • Support Data & AI strategy and roadmap development, including AI use case identification and prioritization, strategic themes, and defining the roadmap to achieve the target state;
      • Contribute to target state Data & AI architecture, including scalable data and AI pipelines, platform capabilities, integration patterns, and the overall architecture required to support analytics and AI at scale;
      • Provide input into Data & AI governance and operating models, including responsible AI principles, security controls, data and AI sovereignty, and the roles, processes and capabilities required to operate Data & AI effectively;
      • Present and explain technical work to clients, including walking non-technical stakeholders through how a solution works and why it was built that way;
      • Contribute across the solution lifecycle from requirements and architecture through development, testing, deployment, and production support.
      Eligibility Requirements
      • Bachelor’s or Master’s degree  in computer science, Software Engineering, Data Science or a related field.
      • At least two years of relevant professional experience building AI or machine learning applications.
      • Practical experience with LLMs and generative AI applications, including at least one agentic framework such as LangChain, LangGraph, LlamaIndex or CrewAI.
      • Experience building RAG solutions, including embeddings, semantic search and vector databases such as Azure AI Search, Pinecone, Qdrant, Weaviate or Milvus.
      • Knowledge of or practical experience with MCP (Model Context Protocol) and MCP servers/tools.
      • Good SQL, comfortable with both relational and NoSQL databases, and an understanding of data lakes and warehouses and how AI applications connect to them.
      • Familiarity with Git, Docker, CI/CD, testing, and software engineering best practices.
      • Strong communication skills articulate, comfortable interacting with clients, and able to translate business requirements into practical technical solutions.
      • Comfortable working across more than one client engagement at a time and adapting as priorities shift.
      • Strong attention to detail, problem solving ability, and a collaborative mindset, with the ability to work independently while contributing effectively as a team player.
      Preferred Qualification
      • Strong written and verbal communication skills, with the ability to prepare high-quality technical documentation, presentations, architecture diagrams, and client facing Data & AI deliverables.
      • Experience with cloud AI services such as Azure OpenAI, Azure AI Foundry, Amazon Bedrock or Vertex AI.
      • Experience with workflow automation platforms such as n8n, Make or Power Automate.
      • Experience with PostgreSQL, SQL Server, MongoDB, Redis or similar.
      • LLM evaluation, observability, guardrails, prompt engineering and hallucination mitigation.
      • Understanding of ETL/ELT, data pipelines, data quality and data governance.
      • Familiarity with frontend technologies such as React or Next.js.
      • Exposure to AI governance, privacy and security compliance standards such as ISO 27001 or SOC 2.
      Deadline

      Send us your CVs / Resume at pk-fmhrdesk@kpmg.com  with “AI Engineer: Agentic AI & Full Stack AI Solution” mentioned in subject of the email latest by 21 September 2026.