4Bell Technology
Senior AI/ML Engineer(R-2018)
100,000.00-3,000,000.00/A
Any Degree
IT (Information Technology)
Full-time
Hyderabad
10-Oct-2026
Python AWS Gen AI Agentic AI LLM MCP Server RAG Eks Vector Db Pytorch
Job Description
We are looking for high-performing Senior AI Engineers with strong expertise in Agentic AI, MCP servers, and AWS-based ML platforms. This role focuses on building scalable, production-grade AI systems using Python, leveraging LLMs, multi-agent architectures, and cloud-native infrastructure on AWS. Key Responsibilities
• Design and develop agentic AI systems (multi-agent orchestration, reasoning
workflows, tool integrations)
• Build and manage MCP server / model-serving infrastructure
• Develop LLM-powered applications (RAG pipelines, copilots, autonomous
agents)
• Build scalable ML pipelines using Python (training, inference, monitoring)
• Deploy and manage solutions on AWS platform (SageMaker, Bedrock, EKS/ECS,
EC2, S3, Lambda)
• Optimize systems for performance, scalability, latency, and cost
• Implement evaluation frameworks for LLM accuracy, safety, and grounding
• Integrate AI solutions with enterprise systems and APIs
• Collaborate with DevOps teams for cloud-native deployments
• Mentor team members and drive engineering excellence
Mandatory Skills & Experience
• 8+ years of experience in AI/ML engineering or data science
• Strong Python expertise (MANDATORY)
(core programming, ML/AI development, data processing)
• Hands-on experience with LLMs (OpenAI / open-source, prompt engineering,
fine-tuning)
• Proven experience building agentic AI / multi-agent systems
• Experience with MCP servers / model-serving frameworks
• Strong experience with RAG pipelines and vector databases
• Hands-on experience working on AWS platform
(SageMaker, Bedrock, EKS/ECS, EC2, S3, Lambda, IAM)
• Experience with PyTorch / TensorFlow
• Solid understanding of distributed systems and system design
Good to Have
• Experience with LangChain, AutoGen, CrewAI, Semantic Kernel
• Exposure to Amazon Bedrock and GenAI services
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker Pipelines)
• Knowledge of knowledge graphs / semantic search
• Experience in real-time AI / streaming systems