Staff AI Engineer

What you'll do

• Design and build scalable, secure Generative AI solutions using AWS Bedrock and GCP Vertex AI platforms.
• Develop production-grade LLM applications utilizing serverless architectures, event-driven systems, and microservices.
• Architect agentic AI systems to deliver multi-step reasoning and automated workflow orchestration for enterprise use cases.
• Build robust Retrieval-Augmented Generation (RAG) systems using vector databases and custom retrieval pipelines.
• Manage the full machine learning lifecycle including data engineering, model fine-tuning, evaluation, and performance monitoring.
• Ensure all AI solutions comply with HIPAA regulations, data privacy standards, and Responsible AI governance.
• Optimize production workloads for cost, performance, token usage, and latency across cloud environments.
• Mentor engineers and provide technical leadership to shape product roadmaps and reusable platform accelerators.

What we're looking for

• Bachelor’s degree or equivalent experience (HS diploma plus 4 years relevant experience).
• 7+ years of experience in large-scale software development.
• 5+ years of experience in solution architecture or system design.
• 5+ years of experience building large-scale microservices and APIs using Node.js.
• 3+ years of hands-on experience with GCP and AWS, including serverless, event-driven systems, AI/ML, and CI/CD.
• Experience with AWS Bedrock or GCP Vertex AI (or similar technologies) for LLM and GenAI applications.
• Strong experience with Python for AI/ML engineering.
• Production experience with Agentic AI frameworks, RAG architectures, vector databases, and serverless designs.
• Experience with Vertex AI’s Generative AI Studio, vector search orchestration, and agent capabilities (preferred).
• Hands-on experience with vector databases such as OpenSearch, Pinecone, FAISS, pgvector, or Milvus (preferred).
• Strong knowledge of prompt engineering, evaluation, observability, and LLM security patterns (preferred).
• Ability to write design docs, architectural diagrams, runbooks, and technical briefs (preferred).
• Agile/SAFe experience in large enterprises (preferred).
• Cloud certifications from AWS or GCP (preferred).