IN_Associate_ AI Engineer_GCC_Advisory_Bangalore
PwC India (company site, opens in a new tab)4–7 yrsBengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted 8h ago
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Job description
Structured overview of role & requirements
About This Role
- Build and deploy production-ready GenAI solutions, including enterprise RAG systems using LLMs.
- Develop graph-based memory, tool-using agents, and multi-agent orchestration with frameworks such as LangGraph, LangChain, or AutoGen.
- Translate business needs into scalable systems; maintain reliability, performance, and code quality through sound engineering practices.
Minimum Requirements
- Work Experience Required: JD states 2–5 years total experience, including at least 2 years building and deploying GenAI systems; another section states 4–7 years total, so the experience range is inconsistent.
- Hands-on experience with GenAI, LLMs, RAG, and multi-agent frameworks; proficiency in Python and experience with graph-based memory and LLM tool-use patterns.
- Familiarity with cloud-native deployment, such as APIs, containers, or microservices, and software engineering practices including version control, testing, and CI/CD.
- Education listed: BE/BTech, MCA, MTech, MBA, or Master of Engineering; the JD’s degree-field list specifically names MBA, Master of Engineering, and Bachelor of Engineering.
Ideal Candidate Profile
- Has delivered GenAI systems beyond prototypes, with experience deploying and maintaining them in production at scale.
- Strong fit for agentic AI work involving RAG, multi-agent orchestration, tool use, and memory-augmented architectures.
- Can connect business requirements to enterprise-ready technical solutions; experience with cloud LLM services, evaluation, optimization, or prompt engineering is an added advantage.