AI ML Engineer

• JOB DESCRIPTION AI/ML Engineer (2-4 years)
• Job location Bangalore/Coimbatore Work from Office 5days
• Mumbai/Delhi At clients place (Depends on clients work mode)
• What is the role about
• We are seeking a passionate and skilled Senior GenAI Engineer to join our GenAI organization and contribute to ShellKodes next-generation AI initiatives.

This role focuses on building scalable GenAI and Agentic AI solutions using AWS cloud-native services, RAG architectures, and enterprise-grade orchestration workflows. The ideal candidate will have hands-on experience with LLM-based development, agentic frameworks, and AWS Bedrock.

• What you will do
• Design & Development
• Design and develop advanced GenAI solutions including:
• Retrieval-Augmented Generation (RAG)
• Agentic AI workflows (single-agent and multi-agent systems)
• Tool-calling and agent-to-agent orchestration
• Text-to-SQL, IDP (Intelligent Document Processing)
• Summarization, text generation, and multimodal use cases
• Build scalable GenAI services using:
• Amazon Bedrock (mandatory)
• LangChain, LangGraph, AgentCore
• Hugging Face APIs
• AWS cloud services (Lambda, API Gateway, S3, DynamoDB, Step Functions)
• Engineering & Implementation
• Develop backend services and pipelines using Python (FastAPI/Flask).
• Implement embeddings, retrieval pipelines, chunking strategies, and grounding logic.
• Optimize RAG workflows, tool-calling patterns, and agentic reasoning.
• Deploy solutions using AWS-native tooling (SageMaker optional but not required for fine-tuning).
• Execution & Collaboration
• Work closely with technical leads to execute assigned tasks and deliver project modules.
• Participate in requirement discussions, POCs, SOW execution, testing, and production rollout.
• Collaborate with cross-functional teams, including product owners, architects, and customer teams.
• Quality, Performance & Innovation
• Monitor and improve solution robustness, latency, accuracy, and scalability.
• Implement guardrails, enterprise safety practices, and hallucination mitigation patterns.
• Stay updated on emerging LLM models, Bedrock capabilities, agent frameworks, and industry best practices.
• What you will need to have
• Mandatory Experience
• 2 to 4 years of overall engineering experience.
• Minimum 1 year of hands-on GenAI project experience.
• Mandatory Agentic AI experience, including:
• Multi-agent orchestration
• Tool-calling workflows
• Agent reasoning and state management
• Strong hands-on experience with AWS Cloud, including:
• Amazon Bedrock
• Lambda, API Gateway, S3, DynamoDB
• Step Functions / Event-driven architectures (preferred)
• Practical experience with:
• LangChain, LangGraph, AgentCore
• Vector databases (Pinecone, Weaviate, Chroma, Milvus)
• Technical Skills
• Strong Python development experience.
• Knowledge of LLM APIs, embeddings, vector search, and RAG workflows.
• Experience building scalable backend systems and microservices.
• Familiarity with Docker, Git, CI/CD, and cloud-native deployment.
• Soft Skills
• Strong analytical and problem-solving ability.
• Ability to work effectively with cross-functional teams.
• Good communication skills for customer and internal interactions.
• Other Requirements
• Experience in a fast-paced startup or consulting environment is desirable.
• Prior customer-facing experience is an advantage.
• Candidates must be open to working from customer locations (onsite) when required.
• Willingness to travel occasionally for project needs