Data Engineer

Job Title: Senior Gen AI Developer Generative & Agentic AI, and Data Science

Experience Required: 57 Years

Location: Chennai

About the Role

We are looking for an experienced Senior Gen AI developer with Data Scientist background and a strong foundation in machine learning, deep learning, and modern Generative AI systems, with hands-on experience in model deployment.

This role involves designing and implementing AI-driven solutions that combine traditional ML with LLMs and agentic AI frameworks to power intelligent automation, document understanding, and enterprise-grade AI assistants.

Key Responsibilities

1. Generative AI

• Design and fine-tune LLMs (GPT, Claude, Llama, Mistral, etc.) for domain-specific use cases such as document understanding, summarization, and conversational AI.
• Implement retrieval-augmented generation (RAG) pipelines using vector databases (FAISS, Pinecone, Qdrant, Weaviate) and enterprise knowledge bases.
• Develop prompt engineering strategies and evaluate outputs for factual accuracy, coherence, and alignment.
• Experiment with multimodal and diffusion models for image, audio, and text synthesis tasks.

2. Agentic AI Systems

• Build and orchestrate multi-agent frameworks for dynamic decision-making and workflow automation.
• Integrate AI agents with enterprise APIs, databases, and third-party systems to enable autonomous task execution.
• Utilize frameworks such as LangChain, CrewAI, Semantic Kernel, and AutoGen to develop production-ready AI agents.
• Prototype and scale AI copilots and enterprise automation agents for business teams.

3. Core Data Science & ML

• Build, train, and optimize predictive and prescriptive models across regression, classification, and forecasting use cases.
• Perform feature engineering, model evaluation, and interpretability analysis using frameworks like scikit-learn, PyTorch, TensorFlow, or XGBoost.
• Conduct statistical analysis and A/B experiments to validate data-driven decisions.
• Develop MLOps pipelines for scalable and automated model training and deployment.
• Work closely with data engineering teams to prepare high-quality, production-ready datasets from S3, and any of the Redshift, Snowflake, BigQuery, or Synapse.
• Airflow, or Data Factory for ML and GenAI workflows.
• Ensure data lineage, governance, and quality checks for reproducible model outputs.
• Deploy AI models in cloud environments with SageMaker, Vertex AI, or Azure ML.

Category

Tools / Frameworks

Languages

Python, SQL, PySpark

ML/DL

Scikit-learn, PyTorch, TensorFlow, XGBoost

GenAI

OpenAI GPT-4, Claude, Llama, Bedrock, LangChain, Semantic Kernel

Vector Databases

FAISS, Pinecone, Qdrant, Weaviate

Data Platforms

AWS (S3, Glue, Redshift) preferred, or Azure (Data Factory, Synapse), or GCP (BigQuery)

MLOps / CI-CD

MLflow, Docker, Kubernetes, GitHub Actions

Visualization

Streamlit proffered, Good to have - Power BI, Tableau, Plotly

Agentic AI

CrewAI, AutoGen, LangGraph, Semantic Kernel

Interested candidates please share your resume to balkis.begam@terragig.in

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