AI/ML Platform Engineer
Shipping production AI and cloud infrastructure. Multi-model LLM orchestration on AWS Bedrock. Regulated-workload experience from JPMorgan Chase (SOX) and Quality Health Care Group (HIPAA).
What started as Java debugging in a college coffee shop became 6+ years shipping production systems. I build backend services in Python and Java, cloud infrastructure on AWS, and multi-model LLM architectures on Bedrock, with the guardrails, cost budgets, and observability that hold up under real traffic. My instinct is toward systems that operate themselves and AI that ships to real users, not demos.
LinkedIn Profile
Two tenures across regulated workloads: SOX-compliant banking at JPMorgan Chase and HIPAA-compliant healthcare at Quality Health Care Group.
Software Engineer (Banking)
April 2024 - Present
Platform engineering across private and public cloud for SOX-regulated banking services. Jenkins, Spinnaker, Terraform, AWS (Lambda, ECS, Step Functions), Cloud Foundry.
Software Engineer (Healthcare)
June 2018 - April 2024
Sole-developer build of HIPAA-aligned healthcare platform. Django REST Framework + React/TypeScript → Cloud Build (19-step CI/CD) → GCP/AWS.
Cheap models decide yes/no; hard questions climb a ladder. Production pattern from the Healthcare Compliance Platform: multi-model Bedrock routing cut monthly inference costs 78% on HIPAA-regulated document processing. Explore how different request types flow through the tier ladder.
Rates shown are illustrative for tier comparison, not published pricing. Current rates: aws.amazon.com/bedrock/pricing
Healthcare Compliance Platform: production GenAI on HIPAA infrastructure. ARC Modality: multi-tenant AI infrastructure built as independent R&D. Plus earlier social-media + cloud work at Xoobug.
Currently pursuing the AWS Certified Generative AI Developer Professional cert; target June 2026.
Exam code AIP-C01. Covers foundation models, multi-model orchestration, Bedrock integration patterns, prompt engineering, RAG architectures, responsible AI, and production GenAI deployment.
AWS exam details →