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    Job · 14327101

    Price Waterhouse Coopers logo

    GenAI / Agentic AI Automation

    Price Waterhouse Coopers · Hyderabad · hybrid · Posted 55d ago

    Undisclosed5–9 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Senior Associate Forward Deployment Engineer (GenAI / Agentic AI Automation)


    GenAI & Agentic AI Engineering | Forward Deployed Engineering


    Experience : 5 to 9 years


    Locations : Bangalore & Hyderabad


    Job Summary : A senior engineer who owns AI solutions end to end inside a client's environment, from a vague problem to a production-grade deployment. As the technical owner, you will scope, architect, build, and ship GenAI and agentic solutions, and set the approach for evaluation and responsible AI.


    Key Responsibilities

    • Own AI solutions end to end, from discovery to a production-grade deployment on client infrastructure.
    • Design agentic architectures and RAG pipelines that hold up at enterprise scale.
    • Define the approach to prompt engineering, model evaluation, and responsible AI.
    • Integrate solutions into enterprise systems and both structured and unstructured data.
    • Make architecture, technology-selection, and design-review decisions.
    • Work across the full stack to ship end to end.
    • Mentor engineers and raise delivery capability.
    • Codify reusable patterns and share field intelligence with the practice.

    Required Qualifications

    • Substantial software engineering experience with strong hands-on GenAI/agentic work in production.
    • Deep experience with LLMs on AWS Bedrock and provider APIs, and with agent frameworks.
    • Experience designing and deploying enterprise AI applications (agentic workflows, RAG, vector databases, embeddings, semantic search).
    • A solid handle on prompt engineering, model evaluation, and responsible AI in production.
    • Strong full-stack engineering (Python and TypeScript, APIs) and data engineering fundamentals.
    • Ability to navigate ambiguity and drive outcomes at pace.

    Preferred Qualifications

    • AWS AI services (Bedrock, SageMaker).
    • Enterprise AI platforms (Palantir Foundry/AIP, Databricks, Snowflake Cortex).
    • Production deployment (Docker, Kubernetes, CI/CD, Terraform).
    • Experience in regulated industries.
    • A track record as an early engineer or technical founder building from zero to production.
    • AWS Certified Solutions Architect Professional; an AI/ML certification such as AWS Certified Machine Learning – Specialty.

    Technical Skills & Tools

    • LLMs & AI: AWS Bedrock, Anthropic Claude, OpenAI; prompt engineering, model evaluation, responsible AI
    • Agent frameworks & orchestration: LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen; workflow orchestration
    • Retrieval & RAG: embeddings, vector databases (Pinecone, pgvector, Weaviate, Qdrant, OpenSearch), semantic search, rerankers
    • Evaluation & observability: evaluation harnesses, Langfuse, OpenTelemetry
    • Languages: Python, TypeScript / JavaScript
    • Backend & APIs: FastAPI, Node.js, microservices, REST, GraphQL
    • Frontend: React, TypeScript
    • Data: SQL / NoSQL, data pipelines, streaming (Kafka, Kinesis), structured and unstructured data
    • Good to have: AWS SageMaker, Docker, Kubernetes, CI/CD, Terraform, Databricks, Snowflake, Palantir Foundry

    Sourced from naukri

    Skills

    Retrieval Augmented GenerationLangraphaws bedrockLarge Language Models (LLMs)PythonLangchainAgentic AiGenerative Ai

    About PwC

    Price Waterhouse Coopers logo

    Price Waterhouse Coopers

    Management Consulting

    30k+

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    1880

    146 years old

    Bangalore / Bengaluru, Karnataka

    India

    ₹18.4L PA avg

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