Generative AI Architect- Manager

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.

Years of Experience: Candidates with 8+ years of hands on experience

PwC US - Acceleration Center is seeking a visionary Generative AI Architect at the Manager level. In this leadership role, you will design and deploy cutting-edge Generative AI solutions, leveraging technologies like Azure OpenAI Service, GPT models, multi-agent frameworks (LangGraph, CrewAI, AutoGen, etc.) and advanced data pipelines. You will drive innovation through scalable cloud architectures, optimize AI infrastructure, and lead cross-functional teams in implementing transformative AI solutions. The ideal candidate will bring deep expertise in Generative AI technologies, data engineering, Agentic AI and cloud platforms like Microsoft Azure, with a strong focus on operational excellence and ethical AI practices.

Responsibilities

Architecture Design:

• Design and implement scalable, secure, and high-performance architectures for Generative AI applications.
• Integrate Generative AI models into existing platforms, ensuring compatibility and performance optimization.
• Lead development of AI agents capable of orchestrating multi-step tasks—e.g., scheduling, content generation, multi-source integration, etc..
  
  

• Fine-tune pre-trained generative models for domain-specific use cases.
• Data Collection, Sanitization and Data Preparation strategy for Model fine tuning.
• Evaluate, select, and deploy appropriate Generative AI frameworks (e.g., PyTorch, TensorFlow, Crew AI, Autogen, Langraph, Agentic code, Agentflow).
  
  

• Stay up to date with the latest advancements in Generative AI and recommend innovative applications to solve complex business problems.
• Define and execute the AI strategy roadmap, identifying key opportunities for AI transformation.
  
  

• Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.
• Mentor and guide team members on AI/ML best practices and architectural decisions.
• Should be able to lead a team of data scientists, GenAI engineers, devops and Software Developer.
  
  

• Monitor the performance of deployed AI models, agents and systems, ensuring robustness and accuracy.
• Optimize computational costs and infrastructure utilization for large-scale deployments.
  
  

• Ensure compliance with ethical AI practices, data privacy regulations, and governance frameworks.
• Implement safeguards to mitigate bias, misuse, and unintended consequences of Generative AI.
  
  

• Bachelor’s or master’s degree in computer science, Data Science, or a related field.
• 8+ years of relevant technical/technology experience, with significant expertise in GenAI projects with production deployment experience.
• Advanced programming skills in Python and fluency in data processing frameworks like Apache Spark.
• Should have strong knowledge on LLM’s foundational model (OpenAI GPT4o, O1, Claude, Gemini etc), while need to have strong knowledge on opensource Model’s like Llama 3.2, Phi etc.
• Experience developing an efficient system design for Agentic architecture and implementing orchestration of agents and sharing memory across agents.
• Proven track record with event-driven architectures and real-time data processing systems.
• Familiarity with Azure DevOps and other LLMOps tools for operationalizing AI workflows.
• Deep experience with Azure OpenAI Service and vector DBs, including API integrations, prompt engineering, and model fine-tuning. Or equivalent tech in AWS/GCP.
• Knowledge of containerization technologies such as Kubernetes and Docker.
• Comprehensive understanding of data lakes and strategies for data management.
• Expertise in LLM frameworks including Langchain, Llama Index, and Semantic Kernel.
• Proficiency in cloud computing platforms such as Azure or AWS.
• Exceptional leadership, problem-solving, and analytical abilities.
• Superior communication and collaboration skills, with experience managing high-performing teams.
• Ability to operate effectively in a dynamic, fast-paced environment.
  
  

• Experience with additional technologies such as Datadog, and Splunk.
• Familiarity with emerging Model Context Protocols (MCP) and dynamic tool integration to build flexible agentic systems
• Possession of relevant solution architecture certificates and continuous professional development in data engineering and GenAI.
  
  

• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA/ Any Degree