AWS GenAI Engineer

Opportunity details

Must-have skills

• Must-have skills include AI frameworks, Copilot, AI/ML, GenAI, machine learning, RAG, SageMaker, Google or AWS cloud servers, GitHub, and Python.

Key responsibilities

• Design and develop generative AI applications using Amazon Bedrock, Bedrock AgentCore, and foundation models.
• Build RAG pipelines with Bedrock Knowledge Bases, agentic retrieval, smart parsing, and multimodal content support.
• Develop and deploy custom ML models with SageMaker, including training and fine-tuning through JumpStart and HyperPod.
• Implement prompt optimization, fine-tuning, Intelligent Prompt Routing, Bedrock Guardrails, content safety, PII filtering, and hallucination mitigation.
• Connect enterprise sources such as S3, SharePoint, Confluence, Google Drive, OneDrive, and web crawlers to Knowledge Bases.
• Evaluate, benchmark, and A/B test foundation models and integrate GenAI into production applications.
• Provide technical guidance to associates on AI and ML best practices.

Required qualifications

• Bachelor's degree in Computer Science, Data Science, AI/ML, or a related field.
• At least 5 years of software engineering or ML engineering experience and at least 3 years of hands-on AWS AI/ML services experience.
• Strong experience with Amazon Bedrock, foundation models, SageMaker, RAG pipelines, Bedrock Knowledge Bases, vector stores, Python, and ML frameworks.
• Experience with orchestration frameworks, prompt engineering, model evaluation, LLM architectures, tokenization, inference optimization, and Bedrock Guardrails.
• Knowledge of AI/ML data engineering, including ETL, data preprocessing, and feature engineering.
• Strong communication skills and the ability to articulate technical decisions.

Nice-to-have qualifications

• AWS Machine Learning Specialty or AI Practitioner certification.
• Experience with multimodal AI, SageMaker MLOps pipelines, model monitoring, AI observability, GitHub Copilot, Cursor, or Amazon Q Developer.
• Knowledge of responsible AI frameworks, Automated Reasoning, and bias mitigation.

Work arrangement

• The opportunity type is explicitly listed as hybrid in the Asia/Kolkata time zone.

Application process

• Applicants are directed to register or log in, complete a screening form, upload an updated resume, and proceed through client interviews.