PFB and kindly connect and let me know if interested or Share your CV on [email protected] or if you have any references it will be helpful.

Responsibilities:

- Collaborate with cross-functional teams to understand business requirements and identify opportunities to apply Agentic AI and Generative AI (GenAI) solutions to solve complex enterprise problems.
- Design, develop, and implement advanced GenAI and Agentic AI systems, including ReAct agents (Reasoning + Acting frameworks), multi-agent architectures, and autonomous AI workflows.
- Build and deploy intelligent AI-powered chatbots and conversational agents using LLMs, tool-calling frameworks, retrieval-augmented generation (RAG), memory modules, and agent orchestration patterns.
- Ensure consistency, reliability, and alignment in AI-generated outputs through prompt engineering, evaluation frameworks, guardrails, and monitoring mechanisms.
- Develop and implement machine learning models and algorithms to support GenAI applications, including fine-tuning, embeddings, and hybrid AI architectures.
- Perform data cleaning, preprocessing, and feature engineering to prepare structured and unstructured data for machine learning and GenAI pipelines.
- Collaborate with data engineers to design efficient data pipelines and integrate ML/LLM systems into scalable production environments.
- Validate and evaluate model and agent performance using appropriate metrics (accuracy, latency, hallucination rate, consistency scoring, human evaluation frameworks).
- Develop and deploy production-ready AI applications using object-oriented programming principles, ensuring modularity, scalability, maintainability, and robustness.
- Implement containerized AI solutions using Docker and Kubernetes for orchestration, scaling, and cloud-native deployments.
- Design and implement tool-augmented agents, API-integrated workflows,



and autonomous decision-making systems using contemporary AI agent frameworks.
- Create dashboards, reports, and visualizations to communicate AI insights and business impact clearly to technical and non-technical stakeholders.
- Continuously stay updated with advancements in GenAI, Agentic AI, multi-agent systems, LLM orchestration, and emerging AI frameworks, recommending innovative approaches to enhance enterprise AI capabilities.

Requirements:

- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
- 7+ years of relevant technical/technology experience, with a focus on GenAI projects.
- Robust programming skills in languages such as Python, R, or Scala.
- Proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Experience with data preprocessing, feature engineering, and data wrangling techniques.
- Solid understanding of statistical analysis, hypothesis testing, and experimental design.
- Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud.
- Knowledge of data visualization tools and techniques.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to work in a fast-paced and dynamic environment.
- Experience with object-oriented programming languages such as Java, C++, or C#. Experience developing and deploying machine learning applications in production environments.

- Understanding data privacy and compliance regulations.




- Relevant certifications in data science or GenAI technologies.
- Development experience in system designing, proven track record of software delivery through all phases of development, critical thinking, ability to clearly communicate, present and lead.

Nice to Have Skills:

- Experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock.
- Familiarity with LLM backed agent frameworks such as Autogen, Langchain, Langgraph Semantic Kernel, etc.
- Experience in chatbot design, frontend and development.
- Certification of cloud or Genai
- Designed and implemented enterprise-grade GenAI solutions using Databricks Mosaic AI, enabling scalable LLM deployment and governance.
- Built Retrieval-Augmented Generation (RAG) pipelines using Mosaic AI Vector Search and Foundation Models for domain-specific knowledge querying.
- Fine-tuned and deployed LLMs using Mosaic AI Model Serving, optimizing inference latency and cost.
- Implemented secure LLM workflows with Unity Catalog governance and model tracking via MLflow.
- Strong background in the Healthcare domain, with deep understanding of Payer operations and working knowledge of Provider ecosystems.
- Experience in consulting engagements, including direct interaction with client stakeholders and managing client relationships.
- Demonstrated leadership experience managing and mentoring teams of 510 members.

If you are passionate about GenAI technologies and have a proven track record in data science, join PwC US - Acceleration Center and be part of a energetic team that is shaping the future of GenAI solutions.

We offer a collaborative and innovative work environment where you can make a significant impact.

Preferred Qualifications:

- BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Masters Degree /MBA from reputed institute

📌 PLS LLM Engineer (Bengaluru)
🏢 PwC
📍 Bengaluru