Senior Gen AI Engineer

Soothsayer Analytics; Hyderabad; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

Soothsayer Analytics in Hyderabad seeks a Senior Gen AI Engineer with strong ML fundamentals and data engineering expertise to lead scalable AI/LLM solutions. You will design, fine-tune, and deploy models (LLMs, RAG) while ensuring robust data pipelines and MLOps practices.

Responsibilities include agentic AI and workflow design, AI orchestration with LangGraph, integration of Agents, Tools and Chains, production MLOps and deployment, CI/CD with GitHub, containerization with Docker and

Qualifications

• 6+ years in ML + data engineering; 2+ years in LLM/GenAI projects; 3+ years building ML models.
• Hands-on experience with production ML workflows, MLOps, and deployment pipelines.
• Experience integrating AI models into scalable production systems.

Responsibilities

• Lead design and implementation of Agentic AI systems and multi-step workflows.
• Build AI orchestration systems using LangGraph and integrate Agents, Tools and Chains.
• Implement A2A communication and MCP for inter-model interactions.
• Develop production-grade MLOps, CI/CD pipelines, testing, and observability.
• Containerize models with Docker and deploy on cloud via Kubernetes.

Skills

ML Fundamentals

Data Engineering

LLM/GenAI

MLOps

Prompt Engineering

Tools

Docker

Kubernetes

LangGraph

HuggingFace

Pinecone

Weaviate

Job description

We seek a Senior Gen AI Engineer with strong ML fundamentals and data engineering expertise to lead scalable AI/LLM solutions.

• This role focuses on integrating AI models into production, optimizing machine learning workflows, and creating scalable AI-driven systems.
• You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices.
• Key Responsibilities Agentic AI & Workflow Design: Lead design and implementation of Agentic AI systems and multi-step AI workflows.
• Build AI orchestration systems using frameworks like LangGraph.
• Utilize Agents, Tools, and Chains for complex task automation.
• Implement Agent-to-Agent (A2A) communication and Model Connect Protocol (MCP) for inter-model interactions.
• Production MLOps & Deployment: Develop, train, and deploy ML models optimized for production.
• Implement CI/CD pipelines (GitHub), automated testing, and robust observability (monitoring, logging, tracing) for Gen AI solutions.
• Containerize models (Docker) and deploy on cloud (AWS/Azure/GCP) using Kubernetes.
• Implement robust AI/LLM security measures and adhere to Responsible AI principles.
• AI Model Integration: Integrate LLMs and models from HuggingFace.
• Apply deep learning concepts with PyTorch or TensorFlow.
• Data & Prompt Engineering: Build scalable data pipelines for unstructured/text data.
• Design and implement embedding/chunking strategies for scalable data processing.
• Optimize storage/retrieval for embeddings (e.g., Pinecone, Weaviate).
• Utilize Prompt Engineering techniques to fine-tune AI model performance.
• Solution Development: Develop GenAI-driven Text-to-SQL solutions.
• 6+ years in ML + data engineering , with 2+ years in LLM/GenAI projects. 3+ years developing machine learning models. _