Specialist- Data Science

3 days ago

Pune, Maharashtra, India Atomberg Technologies Full time

Role & responsibilities:

Must Have Skills

Artificial Intellige..

Secondary Skills

N/A

Job Description

Overview

We are looking for a Generative AI Engineer who specializes in building, integrating, and deploying advanced GenAI systems. The ideal candidate has hands-on experience with large language models, Retrieval-Augmented Generation (RAG), multi-agent AI systems, vector databases, and cloud AI platforms. This role focuses on designing intelligent, production-grade GenAI solutions that power next-generation applications.

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Key Responsibilities

Generative AI Development

Build and deploy applications powered by state-of-the-art LLMs, including GPT, Llama, Claude, and other foundation models.

Design and implement prompt engineering, prompt optimization, and model orchestration workflows.

RAG Systems & AI Agents

Architect and implement RAG pipelines using embeddings, chunking strategies, and semantic search.

Develop agentic AI systems and multi-agent architectures for automation, reasoning, and task delegation.

Leverage LangChain, HuggingFace, and similar frameworks to build contextual, memory-enhanced AI behaviours.

Model Evaluation & Selection

Evaluate, benchmark, and compare foundation models to determine the best fit for specific applications.

Perform A/B testing, latency evaluation, cost analysis, and quality assessment of LLM-powered systems.

Monitor and improve generative output quality using structured evaluation frameworks.

Data & Infrastructure for GenAI

Prepare and curate datasets suitable for LLM workflows, including text normalization, embeddings, vector storage, and retrieval mechanisms.

Work with vector databases (Pinecone, Weaviate, Chroma, Milvus) and traditional SQL/NoSQL DBs.

Use cloud AI platforms such as Amazon Bedrock for scalable model deployment and inference.

Architectural & Strategic Contribution

Apply first-principles thinking to determine when GenAI is the right solutionand when it isnt.

Collaborate with product, engineering, and data teams to design end-to-end GenAI systems.

Ensure responsible and efficient use of LLMs within production environments

Preferred candidate profile:

Strong proficiency in Python with experience building GenAI applications.

Hands-on expertise with LLMs, RAG pipelines, AI agents, and multi-agent systems.

Experience with AI frameworks: PyTorch, TensorFlow, HuggingFace, LangChain, scikit-learn, Transformers.

Familiarity with LLM APIs (OpenAI, Anthropic, Amazon Bedrock, etc.).

Understanding of embeddings, semantic search, chunking, and vector indexing.

Experience with SQL, NoSQL, and vector databases.

Solid grounding in ML/DL/NLP fundamentals to support GenAI system design.

Strong analytical skills and the ability to choose optimal GenAI solutions using first-principles reasoning.

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