AI/ML Specialist / GenAI Lead /Agentic AI Engineer with Python

Vibehackers; Hyderabad; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Vibehackers in Hyderabad, India, is seeking a senior AI/ML Specialist / GenAI Lead to design, develop, and deploy production-grade AI solutions using LLMs and agentic AI frameworks. You will lead teams and operationalize ML pipelines in a demanding on-site role.

Responsibilities include building RAG and agentic systems, applying prompt engineering, and guiding architectural decisions for real-time inference with containerization (Docker, Kubernetes).

Qualifications

• 9+ years overall AI/ML experience with 4–5 years hands-on work.
• Strong foundation in ML fundamentals, NN architectures, and attention mechanisms.
• Hands-on with LLMs (GPT-4, Claude, Llama, Mistral, Gemini) and prompt engineering.

Responsibilities

• Design end-to-end ML/AI solutions, including RAG and agentic AI systems.
• Develop and integrate LLM-based applications using advanced prompting.
• Lead model selection, fine-tuning, optimization, and deployment.
• Build and maintain ML pipelines, CI/CD, model versioning and monitoring.
• Mentor AI/ML teams; make architectural and strategic tech decisions.
• Implement containerization and orchestration for production workloads.

Skills

Technical leadership

Mentoring

Prompt engineering

RAG systems

Agentic AI

Deep learning

MLOps

Tools

Docker

Kubernetes

LangChain

PyTorch

TensorFlow

Hugging Face

Job description

AI/ML Specialist / GenAI Lead /Agentic AI Engineer with Python

Uses LLMs, LangChain, and agentic AI frameworks—directly aligned with vibe coding and rapid AI prototyping.

About the Role

Lead GenAI/Agentic AI engineering role to design, develop, and deploy production-grade AI solutions using LLMs and modern AI tooling. The position focuses on building RAG and agentic systems, leading teams, and operationalizing ML pipelines in a Hyderabad on-site role.

Job Description

Role

We are hiring a senior GenAI / Agentic AI Engineer to design, develop, and implement production-grade AI solutions. The role centers on building systems that leverage large language models, agentic AI frameworks, and retrieval-augmented generation to solve real-world problems, and includes technical leadership responsibilities.

Key Responsibilities

• Design and implement end-to-end ML/AI solutions, including RAG and agentic AI systems.
• Develop and integrate LLM-based applications using prompt engineering and advanced prompting techniques.
• Lead model selection, fine-tuning, optimization, and deployment for performance and latency requirements.
• Build and maintain ML pipelines, CI/CD for ML, model versioning, monitoring, and observability.
• Mentor and lead AI/ML engineering teams; make architectural and strategic technology decisions.
• Implement containerization and orchestration for production workloads (Docker, Kubernetes).

Requirements

• 9+ years of overall experience with relevant AI/ML experience; 4–5 years of hands-on AI/ML experience indicated.
• Deep knowledge of ML fundamentals, algorithms, statistical modeling, and neural networks.
• Advanced understanding of deep learning architectures (CNNs, RNNs, Transformers) and attention mechanisms.
• Hands-on experience with LLMs (GPT-4, Claude, Llama, Mistral, Gemini) and prompt engineering (listed as compulsory).
• Experience with Retrieval-Augmented Generation (RAG) and agentic AI frameworks (compulsory).
• Experience designing and deploying production ML systems, including real-time inference optimization.
• Proven technical leadership and prior experience leading/mentoring teams (3+ years in leadership roles desirable).

Preferred / Nice-to-have

• Experience with fine-tuning techniques such as LoRA, QLoRA, PEFT.
• Knowledge of model compression, quantization, and optimization.
• Familiarity with MLOps tools and model observability.

Technical Stack

• Languages & frameworks: Python, PyTorch, TensorFlow, JAX, Hugging Face Transformers
• Messaging / streaming: Kafka

Location & Employment

• Employment type: Permanent; Work From Office

Python Kafka LangChain LangGraph Autogen CrewAI PyTorch TensorFlow JAX Hugging Face Transformers Pinecone Chroma FAISS MLflow LangSmith Kubeflow AWS SageMaker AWS Bedrock Azure ML Google Cloud Vertex AI Docker Kubernetes LoRA QLoRA PEFT GPT-4 Claude Llama Mistral Gemini RAG AgenticAI

Skills

Machine Learning Deep Learning Natural Language Processing Computer Vision Prompt Engineering Model Optimization MLOps CI/CD Containerization Real-time Inference Optimization System Design Technical Leadership Team Mentoring Architectural Thinking Strategic Decision Making