IN_Manager_Gen AI_Data and Analytics_Advisory_Hyderabad

Line of Service Advisory

Industry/Sector Not Applicable

Specialism Data, Analytics & AI

Management Level Manager

Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

* 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 purpose-led and values-driven 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 .At  PwC , we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. “

Role Overview

 

 

The   Technical

  Product Owner / Forward Deployed   Engineer

  operates at the intersection of   product strategy, technical solution architecture, and GenAI   ecosystem , driving the design, deployment, and optimization of AI-powered solutions within Portfolio Services. This role requires fluency in   agentic AI orchestration, enterprise-grade system integration, and cloud-native deployment , ensuring solutions are technically robust, scalable, and aligned with client value delivery.  

 

Responsibilities

 

 

Product Strategy & Architecture 

• Define and maintain the   technical product roadmap

    for AI agents, automation pipelines, and orchestration frameworks.

• Translate business requirements into   solution architectures

    with clear data flows, API contracts, and integration points.

• Develop   user stories and acceptance criteria

    with explicit technical dependencies and performance benchmarks.

• Balance   short-term MVP delivery

    with long-term scalability, modularity, and extensibility.

Technical Deployment & Engineering 

• Lead   end-to-end deployment

    of AI/GenAI solutions, including containerization, CI/CD pipelines, and cloud-native rollout.

• Configure and integrate   LangGraph,   LlamaIndex, Hugging Face models, TensorFlow/PyTorch   pipelines

    into enterprise workflows.

• Implement   data ingestion pipelines, vector databases (e.g., Pinecone,   Weaviate), and RAG architectures

    for production-grade AI agents.

• Troubleshoot   low-level system issues

    (API failures, latency bottlenecks, memory leaks) and provide root-cause analysis.

• Build   POCs and MVPs

    with measurable KPIs (latency, throughput, accuracy, adoption).

Stakeholder Engagement & Change Management 

• Partners with   Transaction Management, Lease Administration, and Consulting teams

    to map workflows into technical blueprints.

• Deliver   training sessions

    on AI agent orchestration, prompt engineering, and system integration.

• Collect   post-deployment telemetry

    (usage logs, error rates, adoption metrics) and iterate solutions accordingly.

• Communicate   architecture decisions, trade-offs, and technical risks

    to leadership and cross-functional teams.

Governance & Quality Assurance 

• Ensure compliance with   enterprise security standards, data governance policies, and ethical AI guidelines …