Internal Firm Services
Industry/Sector
& Summary
In ServiceNow consulting at PwC, you will gain extensive experience in ServiceNow applications and assist clients in optimising operational efficiency through analysis, implementation, training, and support tailored to ServiceNow software.
Why PWC
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purposeled and valuesdriven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us .
& Summary
We are seeking a Senior AI Engineer/Architect with deep technical expertise in architecting and building resilient, productiongrade AI applications using modern GenAI frameworks and RetrievalAugmented Generation (RAG) techniques. This role demands handson expertise in Python, LangChain ecosystem (LangFlow, LangGraph, LangFuse), and Vector Databases such as Azure AI Search, Qdrant, and the likes. The ideal candidate should be capable of architecting intelligent, highly performant AI agentbased systems that combine LLMs with semantic search, tool orchestration, and business logic.
- Design, develop and deploy LLMpowered intelligent agents and RAGbased applications using frameworks like LangChain, LangFlow, and LangGraph.
- Implement LangFuse for observability, latency tracking, and hallucination detection in GenAI pipelines.
- Build scalable semantic search pipelines using vector databases such as Qdrant, Pinecone, Azure AI Search, and integrate with LLMdriven workflows.
- Develop Pythonbased microservices for embedding AI capabilities into enterprisegrade platforms using frameworks such as FastAPI, FastMCP, Flask, or Django.
- Leverage OpenAI, Gemini, Claude, or opensource LLMs (e.g., LLaMA, PaLM, Mistral) via APIs or selfhosted models for multiturn conversations and knowledgedriven tasks.
- Construct multihop reasoning, toolcalling agents capable of realworld decisionmaking across domains like customer support, marketing, and operations.
- Automate deployment of AI solutions, using Azure DevOps or GitHub Enterprise and GitHub Actions.
- Effectively collaborate with data engineers, AI developers and product teams to review existing AI Solutions architecture and identify technical alternatives to improve nonfunctional capabilities of existing solutions.
- Align GenAI solutions with business use cases and ensure robust delivery pipelines.
- Define and implement inhouse evaluation metrics for latency, grounding, factual consistency, and user engagement.
Mandatory skill sets
- Proficiency in Python with a strong understanding of data structures, concurrency, and REST API development and deployments on Serverless environments on Microsoft Azure.
- Extensive, handson experience with GenAI tools Predominantly,
- LangChain (Agents, Chains, Callbacks, Tools),
- LangFlow (Visual orchestration of agent workflows),
- LangGraph (Stateful graphbased agent routing),
- LangFuse (Monitoring & Evaluation).
- Proven experience with RAGbased system design, including chunking, embedding generation, retrieval strategies (dense, hybrid), and feedback loops.
- Exposure to Azure AI Services like AI Search (formerly Cognitive Search), Document Intelligence.
- Exposure to Microservicesoriented and Containerized deployment architecture leveraging Azure Kubernetes Services (AKS)
- Handson with Vector Stores Qdrant, Azure AI Search, Pinecone, Chroma, Weaviate.
- Solid understanding of Embedding Models, Chat
Completion Models, LLM token limits, context windowing, and semantic similarity techniques. - Knowledge of OpenAI API, LiteLLM, Hugging Face Transformers, and LLM finetuning & evaluation.
- Extensive experience building and deploying LLM solutions in cloud environments like Azure.
- Exposure to observability tooling and latency optimization strategies in GenAI pipelines.
- Experience in prompt engineering, context synthesis, and fewshot learning patterns.
- Working knowledge of CI/CD pipelines to deploy AI solutions, using Azure DevOps or GitHub Enterprise and GitHub Actions.
Preferred skill sets
Azure Devops, AI
Years of experience required
8+ yrs
Education qualification
Bachelors
Education
Degrees/Field of Study required Bachelor Degree
Degrees/Field of Study preferred
Required Skills
Microsoft Azure DevOps
Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, Analytical Thinking, Application Security, Coaching and Feedback, Communication, Configuration Management (CM), Creativity, Cybersecurity, Embracing Change, Emotional Regulation, Empathy, Enterprise Architecture, Human Resources (HR) Consulting, Inclusion, Intellectual Curiosity, IT Change Management, Learning Agility, Optimism, Professional Courage, Relationship Building, Risk Compliance, SelfAwareness {+ 5 more}
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