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JOBDESCRIPTION – AI/ML Engineer (2-4 years)
Job location – Bangalore/Coimbatore – Work from Office – 5days
What is the role about
We are seeking a passionate and skilled Senior GenAI Engineer to join our GenAI organization
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)
Develop backend services and pipelines using Python (FastAPI/Flask).
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.
Experience building scalable backend systems and microservices.
Job ID: 143400441
Skills:
BigQuery, Python, Cloud Functions, GenAI APIs, Vertex AI, Google Kubernetes Engine
Skills:
Git, Azure Functions, Python Programming, FastAPI, MongoDB, Kubernetes, agentic AI solutions, traditional AI algorithms, DevOps practices, AI development workflows, Redis Cache, vector databases, Jupyter Notebook, Relational Databases, ADLS, Azure services, CI CD pipelines, Generative AI LLMs
Skills:
Azure Functions, Azure DevOps, LangChain, Entra ID, Prompt Flow, GPT-4o, ADLS Gen2, Azure Key Vault, Azure Blob Storage, AKS, Azure OpenAI, GPT-4o-mini, Azure Container Apps, Semantic Kernel, LangGraph, GitHub Actions, Azure AI Studio, Azure AI Search, Application Insights, Azure Monitor
Skills:
Machine Learning, Nlp, Pytorch, Cloud Technology, MLops, Python, AWS, Generative AI, Prompt engineering, Distributed training pipelines, Langchain, scikit-learn, LLMOps, Ai, Guardrails, LangGraph, LLM evaluation methodologies, LLM Agentic workflows, LLM technologies, Voice Conversational AI, LlamaIndex, Transformer architectures
Skills:
BigQuery, Python, Cloud Functions, GenAI APIs, Vertex AI, Google Kubernetes Engine