Enterprise Applied AI Solutions Engineer (Implementing Agentic & Generative AI features)
UKG (company site, opens in a new tab)3+ yrsBengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted on 2 Sept
Reach people at UKG
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at UKG you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Build, deploy, and iterate AI-powered features like copilots, summarization, classification, routing, and Q&A to improve internal workflows and employee productivity.
- Develop knowledge-based agents using Retrieval-Augmented Generation (RAG) and design conversational flows for internal functions such as HR helpdesk, including operational agentic or predictive models under guidance.
- Manage AI product feature backlog, coordinate user acceptance testing (UAT), monitor quality and performance, and maintain supporting documentation for deployed AI solutions.
Minimum Requirements
- Minimum 3 years of experience in software engineering or applied solutions development (or equivalent practical experience).
- Proficiency in Python, API integrations; working knowledge of SQL and data access patterns.
- Familiarity with large language models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and agent frameworks like LangChain, LlamaIndex, or Semantic Kernel.
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience).
Ideal Candidate Profile
- Focused on delivering working AI solutions rapidly and iterating based on user feedback rather than theoretical research.
- User-centered with experience mapping workflows and improving productivity in enterprise environments.
- Pragmatic technologist valuing simple, reliable solutions, operational reliability, security compliance, and quality production standards.