Job Description

We are seeking a hands-on Senior AI Engineer to design and build enterprise-grade Agentic AI applications within the AWS ecosystem. The ideal candidate should have solid Python development experience, practical exposure to Large Language Models (LLMs), and hands-on experience building Retrieval-Augmented Generation (RAG) and multi-agent workflows using frameworks such as LangChain/LangGraph or similar. This role focuses on designing, integrating, deploying, and operating AI-powered services on AWS, ensuring scalability, security, reliability, and cost efficiency.

- Design and implement Agentic AI workflows using LLMs (OpenAI, Bedrock, or equivalent).
- Develop Python-based backend services for: Model orchestration, Tool/function calling, Context management, API exposure.
- Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., Pinecone, FAISS, OpenSearch).
- Design secure and scalable AI APIs using AWS services such as Lambda and API Gateway.
- Deploy and manage AI workloads using AWS Bedrock and SageMaker.
- Implement CI/CD pipelines and Infrastructure as Code (CloudFormation/CDK/Serverless Framework).
- Apply MLOps best practices including: Model versioning, Prompt versioning, Monitoring and observability, Logging and performance tracking.
- Ensure AI systems are: Reliable and resilient, Secure (IAM, policies, encryption), Cost-aware and optimized.
- Collaborate with product owners, enterprise application teams, and data engineers to integrate AI solutions into business workflows.




- Contribute to AI use case evaluation and architecture design discussions.

Requirements

- 5 7 years of software engineering experience with strong Python expertise.
- Hands-on experience integrating LLM platforms such as OpenAI or AWS Bedrock.
- Practical experience building: RAG systems, Multi-agent or agentic workflows, Tool-calling or functioncalling architectures.
- Experience with frameworks such as: LangChain / LangGraph (or equivalent orchestration frameworks).
- Solid experience with AWS services: Bedrock, SageMaker (model hosting/inference; full training expertise not mandatory), Lambda, ECS, S3, API Gateway, IAM etc.
- Experience deploying applications using Infrastructure as Code (CloudFormation, CDK, Serverless Framework).
- Understanding of: Prompt engineering, LLM limitations and guardrails, Context window management, Token optimization.
- Familiarity with vector databases and embedding workflows.
- Strong debugging, problem-solving, and system design skills.

Preferred:

- Experience designing secure enterprise AI solutions.
- Exposure to SAP AI, enterprise ERP integration, or business process automation.
- Experience implementing observability for AI systems (latency, hallucination tracking, usage monitoring).
- Experience with TypeScript for AI tooling or frontend integrations.

Disclaimer : This job posting has been aggregated from external source. Role detailscontentand availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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