Design, develop, and deploy scalable Generative AI solutions, including RAG pipelines and Agentic AI workflows. Collaborate with cross-functional teams to integrate LLMs with enterprise data and optimize performance for production environments.
Job Title: Generative AI Engineer
Experience: 6–15 Years
Location: Bengaluru (Remote)
Notice Period: Immediate Joiners
Preferred
Job Overview
We are looking for an experienced Generative AI Engineer
with a strong background in data and hands-on expertise in modern AI
technologies. The ideal candidate should have previously worked as a Data
Analyst, Data Engineer, Data Scientist, or Python Developer and should have
successfully designed and delivered multiple Generative AI solutions.
The candidate must have practical experience in Generative
AI, Retrieval-Augmented Generation (RAG), and Agentic AI, with a proven track
record of delivering at least 3–5 GenAI-based projects or products.
Key Responsibilities
Design, develop, and deploy scalable Generative AI solutions
for business and enterprise use cases.
Build and optimize RAG (Retrieval-Augmented Generation)
pipelines using LLMs and enterprise data sources.
Develop Agentic AI solutions capable of autonomous
reasoning, planning, decision-making, and tool usage.
Design and implement AI agents and multi-agent workflows for
complex business processes.
Integrate Large Language Models (LLMs) with structured and
unstructured enterprise data.
Work closely with Data Engineering, Data Science, and
business teams to identify and develop AI use cases.
Develop APIs and backend services to support GenAI
applications and products.
Evaluate, fine-tune, and optimize LLM performance for
accuracy, relevance, latency, and scalability.
Implement vector search, embeddings, and semantic retrieval
solutions.
Ensure GenAI applications follow best practices related to
security, governance, scalability, and responsible AI.
Take ownership of the end-to-end delivery of GenAI projects
from solution design through production deployment.
Required Skills
6–15 years of overall IT experience.
Strong previous experience in one or more of the following
roles:
Data Engineer or Data Scientist or Data Analyst
Python Developer
Strong hands-on programming experience in Python.
Hands-on experience with Generative AI and Large Language
Models (LLMs).
Strong practical experience in:
Retrieval-Augmented Generation (RAG)
Agentic AI
AI Agents and Multi-Agent Systems
Prompt Engineering
Embeddings and Semantic Search
Vector Databases
Experience with GenAI frameworks such as LangChain,
LangGraph, LlamaIndex, or similar frameworks.
Experience working with LLMs such as OpenAI GPT models,
Claude, Llama, Gemini, or other open-source/commercial models.
Experience with vector databases such as Pinecone, FAISS,
Chroma, Weaviate, Milvus, or similar.
Strong understanding of data processing, data pipelines,
APIs, and databases.
Experience deploying AI/ML or GenAI applications into
production environments.
Knowledge of cloud AI platforms such as AWS Bedrock, Azure
OpenAI, Google Vertex AI, or similar is preferred.
Mandatory Experience
Must have successfully delivered at least 3–5 Generative
AI-based projects or products.
Demonstrated hands-on experience in building and deploying
RAG-based applications.
Demonstrated hands-on experience with Agentic AI or AI Agent
workflows.
Strong data background with previous experience in Data
Engineering, Data Science, Data Analytics, or Python Development.
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