We are looking for an experienced Lead AI Engineer with expertise in building and deploying enterprise-scale Generative AI solutions on AWS. The ideal candidate should have strong hands-on experience with Amazon Bedrock, Amazon SageMaker, and production-grade GenAI implementations, along with proven technical leadership and software engineering expertise.

Key Responsibilities :

- Design, develop, and deploy production-ready Generative AI solutions on AWS.

- Architect scalable AI applications using Amazon Bedrock and Amazon SageMaker.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines and agentic AI solutions.

- Develop enterprise backend services and REST APIs supporting AI applications.

- Lead architecture, design, and implementation of cloud-native AI solutions.

- Automate infrastructure provisioning using Infrastructure as Code (IaC).

- Implement CI/CD pipelines, testing strategies, observability, and secure deployment practices.

- Monitor, optimize, and troubleshoot AI applications for performance, scalability, and cost efficiency.

- Collaborate with cross-functional teams and provide technical leadership throughout the development lifecycle.

- Mentor engineering teams through design reviews, code reviews, and best engineering practices.

Required Skillset :

- 7 - 9 years of overall software engineering, AI, or Machine Learning experience with proven technical leadership.

- Minimum 2 years of hands-on experience delivering production Generative AI solutions.

- Strong experience with Amazon Bedrock, including Converse API, Bedrock Agents, Knowledge Bases, Guardrails, Prompt Management, Model Evaluation, and Flows.

- Hands-on experience with Amazon SageMaker, including model training, fine-tuning, JumpStart, and hosted inference.

- Experience deploying enterprise-scale GenAI solutions on AWS.

- Strong programming skills in Python with experience using AWS SDK (Boto3).

- Experience with Infrastructure as Code (Terraform, AWS CDK, or CloudFormation).

- Strong understanding of LangChain, RAG architectures, agentic AI systems, prompt engineering, and LLM orchestration.

- Expertise in REST API development, enterprise backend development, and cloud-native application design.

- Strong software engineering fundamentals including testing, CI/CD, code reviews, observability, and secure coding practices.

- Experience with CloudWatch, AWS X-Ray, LangSmith, Langfuse, or similar observability tools..