Lead GenAI Engineer

Location: Remote

Job Type: Full-time

Experience: 5–9 years

Cloud Requirement: AWS Mandatory (Amazon Bedrock & SageMaker)

About the Role We need a technical leader to own the architecture and deployment of our Generative AI systems entirely on AWS. This is a hands-on leadership role-you will be making the big architectural calls, mentoring a talented team, and personally building the most complex parts of our GenAI platform. Because our infrastructure is heavily cloud-native, deep and proven, experience with Amazon Bedrock and SageMaker is a hard requirement. If you enjoy owning a GenAI strategy end-to-end and scaling systems securely in the cloud, we want to talk to you.

What You'll Do

• Architect and lead the development of end-to-end GenAI systems, covering everything from data ingestion to deployment and observability.
• Build and scale solutions using Amazon Bedrock and SageMaker JumpStart, while integrating complementary services like OpenSearch Serverless.
• Drive technical direction for complex RAG architectures (GraphRAG, agentic RAG) and multi-agent orchestration.
• Lead and mentor a team of AI engineers and data scientists, growing their technical depth through design and code reviews.
• Own the "FinOps" of our GenAI workloads-managing token economics, caching strategies, and provisioned throughput to keep costs in check.
• Ensure enterprise-grade security and compliance by strictly applying AWS best practices (IAM least-privilege, KMS encryption, VPC isolation).

What We’re Looking For

• 5-9 years in software engineering, ML, or data science, including 1-2+ years operating in a lead or architectural role.
• 2+ years of hands-on experience actively shipping Generative AI products into production.
• AWS Mastery: Extensive, hands-on experience provisioning and scaling models via Amazon Bedrock and SageMaker, alongside strong Infrastructure-as-Code skills (Terraform, CDK).
• High-level proficiency in Python, the AWS SDK (boto3), and building asynchronous APIs (like FastAPI).
• Expertise in agentic workflows (LangGraph, CrewAI) and prompt engineering at scale.
• Excellent communication skills with the ability to translate technical trade-offs to executives and business stakeholders.

Bonus Points If You Have

• Active AWS Certifications (e.g., AWS Certified Machine Learning - Specialty, or Solutions Architect).
• Experience fine-tuning models or managing custom model deployments on Bedrock.
• A background working in regulated industries (healthcare, finance) where navigating strict data privacy compliance is crucial.