Role & responsibilities

Job Summary:

Required Skills and Experience

- Hands-on experience with Amazon Bedrock and Amazon SageMaker.

- Proven ability to deploy, manage, and optimize LLMs and foundation model use cases in AWS.

- Strong experience with MLOps practices in SageMaker, including pipelines, model deployment, monitoring, and governance.

- Experience building, testing, and validating AI/ML solutions in cloud environments.

- Robust understanding of secure AI deployment patterns, IAM, networking, and governed access to AI services.

- Familiarity with model lifecycle management, experimentation, and production AI operations.

- Strong problem-solving skills and ability to work independently in a contractor capacity.

Preferred Qualifications / Certifications





- Relevant AWS certifications preferred, such as:

oAWS Certified Generative AI Developer Professional oAWS Certified Machine Learning Engineer – Associate oAWS Certified Machine Learning – Specialty oAWS Certified AI Practitioner

- Experience with prompt engineering, model evaluation, and AI application integration.

- Exposure to responsible AI, model observability, and deployment validation practices.

- Familiarity with automation and infrastructure-as-code for AWS AI environments.

- Familiarity with FinOps principles and usage in AI workloads.

📌 AWS AI Engineer (Pune)
🏢 Pyramid IT Consulting
📍 Pune