Designed and built Platform-as-a-Service for microservice workloads running on Azure and AWS
to migrate on-prem workloads to the cloud. The platform operates globally, allowing teams to
deploy to several Azure-backed regions worldwide. Helped plan and create regional landing zones
in Azure for application teams wanting to perform globally. Designed platform components using
Terraform, Go, and Node; developed support tooling using Bash, Python, and Azure CLI. De-risk the
platform by addressing security vulnerabilities and ensuring the platform is PCI compliant.
api/devops software engineer @ Harvard Medical School (2 years)
Worked as part of the DevOps team to manage a 15k core CentOS HPC cluster. Designed and implemented
Python-based security scanning pipeline to securely deploy & run Apptainer images via SLURM.
Coordinated cross-team emergency patching efforts. Collaborated with researchers and engineers across
3-letter institutions to deliver secure research infrastructure. Built CI/CD Pipelines with GitHub, Jenkins,
to automate code builds, testing, and deployments. Wrote Puppet modules to manage configuration of HPC fleet.
Wrote custom Puppet module & Python scripts to automatically remediate Tenable findings.
full-stack software engineer @ Global Prior Art (3 years)
Used Django, Celery, Selenium grid, and AWS API Gateway for IP rotation to scrape USPTO patent PDFs,
apply CV for data extraction, and generate reports with relevant claims, saving employees 4-5 hours daily.
Wrote E2E black-box/fuzzing unit tests. Automated on-premise deployment via Github Actions and Ansible.
contributor @ Open-source documentation (5 years)
Contributed hundreds of documentation corrections and enhancements to 400+ open source projects.
Co-creator of Retriever (https://runretriever.app/), an AWS-deployed observability platform that enables AI-powered trace analysis through distributed systems. Built a custom MCP server allowing developers to query trace data using natural language through LLMs like Claude, optimizing context consumption through intelligent data distillation from verbose OTLP structures.
Experienced with building full-stack applications. I am comfortable using AWS as a cloud environment and have experience with AI technologies such as RAG, MCP, and Vector embeddings.
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1 point by zanedev28 62 days ago | parent | context | prev | edit | delete [–] | on: Ask HN: Who wants to be hired? (January 2026)
Co-creator of Retriever (https://runretriever.app/), an AWS-deployed observability platform that enables AI-powered trace analysis through distributed systems. Built a custom MCP server allowing developers to query trace data using natural language through LLMs like Claude, optimizing context consumption through intelligent data distillation from verbose OTLP structures.
Experienced with building full-stack applications. I am comfortable using AWS as a cloud environment and have experience with AI technologies such as RAG, MCP, and Vector embeddings.
Looking for roles in backend engineering, DevOps/SRE, observability, or AI tooling where I can leverage my experience building developer infrastructure and working with distributed systems.
sr. cloud software engineer @ Mastercard (5 years)
api/devops software engineer @ Harvard Medical School (2 years) full-stack software engineer @ Global Prior Art (3 years) contributor @ Open-source documentation (5 years)