IN_Manager_ AI Engineer_GCC_Advisory_Bangalore
PwC India (company site, opens in a new tab)4–7 yrsBengaluruOn-siteDirect career pageEst. 18–35 LPA
Posted 8h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build and deploy production-ready GenAI solutions, especially enterprise RAG systems and LLM applications.
- Implement multi-agent orchestration, graph-based memory and tool-using agents; ensure systems scale reliably and remain maintainable.
- Translate business needs into deployable AI systems, working across functions and applying software engineering practices.
Minimum Requirements
- Work Experience Required: The JD gives conflicting total-experience ranges: 2–5 years in the role description and 4–7 years in the posting details; it requires at least 2 years hands-on building and deploying GenAI systems.
- Hands-on experience with LLMs, RAG and multi-agent frameworks such as LangGraph, LangChain or AutoGen; experience with graph-based memory and LLM tool-use patterns.
- Python proficiency; familiarity with cloud-native deployments (APIs, containers or microservices) and software engineering practices including version control, testing and CI/CD.
- Education listed as required: MBA, Master of Engineering or Bachelor of Engineering; the description also lists BE/BTech/MCA/MTech/MBA.
Ideal Candidate Profile
- Has shipped GenAI systems into production, not only built prototypes, and can address reliability, scale and maintainability.
- Best aligned to agentic AI work combining RAG, orchestration, memory and tool use for enterprise applications.
- Experience with Azure OpenAI, AWS Bedrock, LLM evaluation, optimization or prompt engineering is a shortlist advantage; these are preferred, not stated as mandatory.