Staff AI Engineer — Agentic AI & ML

Job Title: Staff AI Engineer — Agentic AI & ML

Experience: 7-10yrs

Location: Coimbatore (Onsite – 5 Days/Week)

Notice Period: Immediate Joiners Only

About the Role

We are seeking a highly experienced Staff AI Engineer (Lead) to design, build, and scale next-generation agentic AI systems—autonomous solutions capable of reasoning, planning, and executing complex workflows.

In this role, you will lead the architecture and development of AI systems across LLMs, machine learning models, and production-grade infrastructure, while mentoring engineers and driving technical excellence.

Key Responsibilities

• Architect and orchestrate multi-agent AI systems for autonomous task execution

• Design and implement LLM pipelines using frameworks like Lang

Chain, Lang

Graph, and CrewAI

• Build and optimize Retrieval-Augmented Generation (RAG) pipelines

• Integrate external tools and services via APIs, databases, and microservices

• Define and manage agent memory, context handling, and reasoning flows

• Develop, train, and deploy ML models (classification, ranking, anomaly detection)

• Establish robust MLOps pipelines (experiment tracking, monitoring, versioning)

• Fine-tune and optimize models using techniques such as LoRA and quantization

• Lead technical design decisions and mentor a team of AI/ML engineers

Required Qualifications

• 7–10 years of experience in software engineering with 4+ years in AI/ML

• Strong hands-on experience with Large Language Models (LLMs), prompt engineering, and fine-tuning

• Proven expertise in building agentic/autonomous AI systems

• Proficiency in Python and modern AI frameworks (Lang

Chain, Auto

Gen, CrewAI)

• Experience with vector databases and RAG architectures

• Solid understanding of APIs, distributed systems, and cloud platforms (AWS, GCP, Azure)

Core Machine Learning Skills

• Supervised & unsupervised learning techniques

• Frameworks: Py

Torch, Tensor

Flow, scikit-learn, XGBoost

• Strong knowledge of NLP, transformers, and embeddings

• Model evaluation metrics (F1 Score, AUC) and feature engineering

• Experience with scalable data processing tools like Spark or Dask

Preferred Skills

• Familiarity with observability tools such as Lang

Smith and Weights & Biases (W&B)

• Experience with knowledge graphs, reinforcement learning (RLHF, PPO), and multimodal AI

• Contributions to open-source projects or research in AI/ML

Technology Stack

• Languages: Python, Type

Script

• AI/ML: Py

Torch, Tensor

Flow, Hugging Face

• LLMs: OpenAI, Anthropic, Gemini, LLaMA, Mistral

• Data & Vector DBs: Pinecone, Weaviate, Elasticsearch

• MLOps: MLflow, Kubeflow, Airflow

• Infrastructure: Docker, Kubernetes, Terraform, AWS/GCP