Senior AI Engineer - CB

Radial Inc.; Chennai District; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

Radial Inc. seeks a Senior AI Engineer to design, build, and scale enterprise-grade AI solutions across ML, Generative AI, and Agentic AI domains. You will transform business operations with intelligent automation, predictive systems, and AI-powered decision platforms.

You will develop end-to-end ML pipelines, fine-tune models with PyTorch/TensorFlow/Scikit-learn, and implement RAG architectures and autonomous agents using modern toolkits. Production deployment on Kubernetes is expected.

Qualifications

• Proficient Python with hands-on ML experience.
• Experience building end-to-end ML pipelines and deploying models.
• Strong knowledge of ML frameworks and LLM tooling.

Responsibilities

• Design and deploy scalable ML solutions for forecasting, classification, anomaly detection, NLP, and optimization.
• Build end-to-end ML pipelines from ingestion to monitoring and deployment.
• Fine-tune and evaluate models using frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Develop LLM-powered enterprise solutions and autonomous AI agents.
• Implement RAG architectures and multi-agent systems with modern toolkits.
• Deploy AI workloads on Kubernetes/Docker with CI/CD and MLOps pipelines.
• Create APIs and scalable inference services; monitor latency and ROI.

Skills

Python

Tools

TensorFlow

PyTorch

Scikit-learn

XGBoost

LangChain

LlamaIndex

CrewAI

AutoGen

Pinecone

FAISS

Chroma

Weaviate

Kubeflow

SageMaker

Job description

Job Description:

We are seeking a highly capable Senior AI Engineer to design, build, and scale enterprise-grade AI solutions across Machine Learning, Generative AI, and Agentic AI domains. This role requires strong hands-on expertise in ML model development, LLM orchestration, RAG pipelines, autonomous AI agents, and production deployment. You will play a critical role in transforming business operations through intelligent automation, predictive systems, and AI-powered decision-making platforms.

Key Responsibilities

• AI / ML Engineering: Design and deploy scalable machine learning solutions for forecasting, classification, anomaly detection, NLP, and optimization.


• Build end-to-end ML pipelines from ingestion, feature engineering, training, deployment, and monitoring.


• Fine-tune, evaluate, and optimize models using frameworks such as PyTorch, TensorFlow, XGBoost, Scikit-learn.


• Generative AI / Agentic AI: Build LLM-powered enterprise solutions using GPT, Claude, LLaMA, Mistral, Gemini, etc.


• Develop autonomous AI agents capable of planning, reasoning, workflow execution, and tool usage.


• Implement multi-agent systems using CrewAI, AutoGen, LangGraph, LangChain, LlamaIndex.


• Build Retrieval-Augmented Generation (RAG) architectures using vector databases.


• Production & Platform: Deploy AI workloads using Kubernetes, Docker, CI/CD, MLOps pipelines.


• Build APIs and scalable inference services.


• Implement monitoring for latency, hallucination risk, drift, token usage, and ROI.


• Business Collaboration: Partner with product owners, operations teams, and leadership to identify high-value AI opportunities.


• Translate business problems into deployable AI solutions.

Required Skills

• Strong Python expertise


• ML frameworks: TensorFlow / PyTorch / Scikit-learn


• LLM frameworks: LangChain / LlamaIndex / CrewAI / AutoGen


• Vector DBs: Pinecone / FAISS / Chroma / Weaviate


• Cloud: AWS / Azure / GCP


• APIs: FastAPI / Flask / REST / gRPC


• MLOps: MLflow / Kubeflow / SageMaker


• SQL / Spark / Data Engineering fundamentals


• Strong software engineering discipline

Requirements: