Vetted Microservices Professionals

“Software Developer at Amazon Robotics who co-developed a congestion-aware path planning system optimizing robot routes across 23 warehouses. Built and operated a real-time, service-integrated pipeline using AWS (AppConfig, DynamoDB), Java, and Redis caching, and has hands-on experience debugging robot behavior on-site with rigorous testing and staged releases.”

“Spatial computing software engineer focused on making Apple Vision Pro/visionOS accessible, including building VoiceOver and Live Captions features. Debugged a complex Live Captions issue involving dual audio inputs during FaceTime screen sharing by leveraging iOS implementation docs and creating concurrent audio sources; also has safety-critical testing experience from train control systems and is interested in pivoting into robotics.”

“Internship experience deploying cloud-based services into production, including navigating security/resource provisioning and coordinating approvals across impacted teams. Built a Python backend for a local Ollama-based app using open-source models, and has hands-on distributed systems experience implementing and debugging Paxos with extensive logging/state tracing.”

“AWS engineer who productionized an internal ML-driven data pipeline from a notebook prototype into a scalable, observable Python service (schema validation, deduplication, idempotency, safe retries, versioned transforms, CloudWatch alarms), reducing manual effort and improving data accuracy/trust. Experienced diagnosing workflow issues in real time (e.g., upstream schema changes) and partnering with account managers/support to unblock adoption of seller-facing Marketplace features by demonstrating reliability with concrete metrics.”

“Backend/platform engineer with hands-on ownership of Python services (Postgres/Redis/Celery) and measurable performance gains (~20–25%). Strong Kubernetes + ArgoCD GitOps experience delivering zero-downtime rollouts, plus led key reliability fixes (readiness probes, immutable tagging) and supported an on-prem to AWS migration using CDC replication and ALB traffic shifting; also built Kafka real-time analytics pipelines with schema registry.”

“Backend engineer with healthcare platform experience at Thirty Madison, combining Django for secure, data-heavy core services with FastAPI async microservices for real-time patient monitoring. Led Kubernetes migration with Istio service mesh, autoscaling (HPA), and stateful storage patterns, and implemented GitOps CI/CD using ArgoCD. Also built real-time Kafka streaming pipelines with reliability patterns like idempotent producers and offset management.”

“Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.”

“Senior engineering leader in the Bay Area with experience spanning VMware, Hortonworks/Cloudera, Barracuda, and Palo Alto Networks, including leading open-source work (Apache Knox) and architecting large-scale security platforms. Has driven disaster recovery and cloud security products, designed Python microservices for Microsoft 365 security, and scaled teams (3x) while formalizing enterprise readiness practices with automated documentation using Notebook LLM.”

“Entrepreneur building an early-stage community food-sharing, network-effects platform positioned as an alternative to restaurant-centric delivery models (e.g., DoorDash/Uber Eats) by enabling homeowners to act as micro-entrepreneurs. Has been piloting a local community program for nearly a year and uses experiments and customer feedback to validate hypotheses and assess scalability.”

“Backend/data engineer with Optum healthcare claims domain experience building high-reliability Python microservices (FastAPI/Kafka/Postgres) and AWS data platforms (EKS, Glue, Redshift). Demonstrated strong production ownership: fixed duplicate Kafka processing via transactional outbox/idempotency, scaled to millions of daily events, and delivered major SQL performance gains (40+ min to <5 min, ~60% CPU reduction). Seeking remote-only work; targets $130k base.”

“Backend/data engineer with experience building Kafka-driven real-time pipelines that support ML code deployment and downstream integrations. Currently migrating high-throughput mainframe (COBOL/assembly) processing to Java, using Spark/Databricks to preserve performance and employing rigorous A/B testing across dev/pre-prod/prod with years of historical data.”

“Backend/data engineer with production experience at Walmart and HealthSnap building Python services and data pipelines on AWS (EKS, Lambda, Glue, Airflow). Strong reliability and operations focus—implemented idempotency + circuit breakers for peak-traffic consistency issues, GitOps CI/CD, and observability. Demonstrated measurable performance wins (Postgres p95 45s to <5s, ~60% CPU reduction) and modernized SAS batch workflows to Python with parallel-run parity validation and feature-flagged rollout.”

“Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.”

“Backend-leaning engineer with experience at Dropbox, Wayfair, and Etsy who has led cross-product integrations and internal platform tooling. Re-architected a legacy promo code system from a PHP monolith to a Java/Spring Boot microservice achieving a 99% execution-time reduction, and built a React/TypeScript + Supabase product (press.social) with LLM-powered bulk parallel generation and a path to multi-tenancy.”

“Robotics-adjacent software engineer with hands-on ROS 2 experience building and integrating sensor nodes (IMU, GNSS, wheel encoder) and working with distributed pub/sub concepts via ROS IDL and DDS. Also has Gazebo exposure through Udacity coursework and uses Docker as a core development/deployment tool, with related experience in automotive camera-based solutions.”

“Software engineer with 2.5 years at Amazon working on the Package Tracking page (Amazon’s most visited page), delivering new customer actions like Cancel Delivery and Buy Again within a Spring Boot-based stack. Has hands-on experience with feature-flagged rollouts (Weblab), A/B testing, and scaling/load testing for Prime Day-level traffic, and is upskilling into React while leveraging modern AI coding tools on side projects.”

“Backend engineer who built an event-driven, multi-service resume review system integrating AI/ML workflows. Demonstrated strong performance engineering (e.g., composite indexing dropping latency from ~600ms to ~35ms and major P95 gains) and high-throughput pipeline optimization via caching, batching, and worker concurrency tuning, with multi-tenant isolation implemented across DB and Redis.”

“Former multi-startup CTO with experience supporting successful capital raises and working directly with boards/investors. Known for implementing operational systems that reduce client escalations (e.g., a status/semaphore overview board) and for building UX-forward MVPs that evolve into automated platforms, including a loan underwriting system for a small US lender.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”