IN_Senior Associate_ AI Engineer_GCC_Advisory_Bangalore
PwC India
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Job summary
PwC Bengaluru is seeking a passionate AI Engineer with 2–5 years of GenAI experience to join our AI/ML team. You will design, develop, and deploy GenAI solutions, focusing on production-ready GAI workflows, RAG systems, and multi-agent orchestration.
The role requires strong Python skills, cloud-native deployment experience, and collaboration across cross-functional teams to deliver scalable GenAI-powered data solutions for clients.
Qualifications
- 2–5 years of total experience in AI/ML or software engineering.
- Minimum 2 years of hands-on GenAI system development.
- Experience with LLMs such as GPT-4, Claude 2/Gemini, etc.
- Strong knowledge of RAG systems and multi-agent frameworks like LangGraph, LangChain, or AutoGen.
- Proficiency in Python and cloud-native deployments.
- Solid software engineering practices: version control, testing, CI/CD.
- Experience with graph-based memory and LLM tool-use patterns.
Responsibilities
- Design, develop, and deploy GenAI solutions with production readiness.
- Build and scale Retrieval-Augmented Generation (RAG) systems for enterprise use cases.
- Integrate with graph-based memory and tool-using agents to enhance LLM capabilities.
- Implement multi-agent orchestration and reasoning systems.
- Use LLM frameworks and libraries (LangChain, AutoGen, LangGraph).
- Write clean, efficient, scalable Python code; collaborate across teams.
- Ensure system scalability, reliability, and maintainability through engineering best practices.
Skills
Education
Tools
Job description
Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in intelligent automation at PwC will focus on conducting process mining, designing next generation small- and large-scale automation solutions, and implementing intelligent process automation, robotic process automation and digital workflow solutions to help clients achieve operational efficiencies and reduce costs. *WhyPWC AtPwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour 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 foreach other. Learn more about us. AtPwC, 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. Job Decription and Summary We are seeking a passionate and skilled AI Engineer with 2–5 years of experience, including a minimum of 2 years in Generative AI (GenAI), to join our AI/ML team. The AI Engineer will play a key role in building and deploying advanced AI solutions leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), multi-agent frameworks, and state-of-the‑art tooling. Responsibilities: Design, develop, and deploy GenAI solutions, with a focus on real‑world production readiness. Build and scale Retrieval-Augmented Generation (RAG) systems for enterprise use cases. Integrate with graph‑based memory and tool‑using agents to enhance LLM capabilities. Implement multi‑agent orchestration and reasoning systems (e.g., AutoGen , LangGraph , custom agents). Use LLM frameworks and libraries (e.g., LangChain , AutoGen , LangGraph etc.). Write clean, efficient, and scalable code in Python (or other languages as needed). Collaborate across cross‑functional teams to translate business needs into scalable GenAI‑powered systems. Ensure system scalability, reliability, and maintainability through strong software engineering practices.
- Design, develop, and deploy GenAI solutions, with a focus on real‑world production readiness.
- Build and scale Retrieval-Augmented Generation (RAG) systems for enterprise use cases.
- Integrate with graph‑based memory and tool‑using agents to enhance LLM capabilities.
- Implement multi‑agent orchestration and reasoning systems (e.g., AutoGen , LangGraph , custom agents).
- Use LLM frameworks and libraries (e.g., LangChain , AutoGen , LangGraph etc.).
- Write clean, efficient, and scalable code in Python (or other languages as needed).
- Collaborate across cross‑functional teams to translate business needs into scalable GenAI‑powered systems.
- Ensure system scalability, reliability, and maintainability through strong software engineering practices.
- 2–5 years of total experience in AI/ML or software engineering.
- Minimum 2 years of hands‑on experience in building and deploying GenAI systems.
- Experience in working with LLMs such as GPT-4, Claude 2/Gemini, etc.
- Strong hands‑on knowledge of RAG systems and multi agent frameworks like LangGraph , LangChain , or AutoGen ..
- Proficiency in Python and familiarity with cloud‑native deployments (e.g., APIs, containers, microservices).
- Solid understanding of software engineering best practices, including version control, testing, and CI/CD.
- Experience in working with graph‑based memory and LLM tool use patterns.
- Experience with tool‑using agents, memory‑augmented architectures, or cognitive architectures.
- Prior contributions to open‑source GenAI or agent frameworks.
- Familiarity with Azure OpenAI, AWS Bedrock, or other cloud‑based LLM services.
- Background in optimization, evaluation, and prompt engineering for LLM systems.
- Experience in deploying AI systems in production environments and maintaining performance at scale
- Work with cutting‑edge GenAI and agentic AI tools.
- Contribute to real‑world, scalable AI solutions.
- Opportunity to innovate and build next‑gen intelligent systems.
- Collaborative, growth‑oriented environment.
- GenAI and Agentic AI
- GenAI and Agentic AI
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