Gen AI Engineer
NewBe an early applicantJob 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.
- 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.