Vetted Distributed Systems Professionals

“Engineering leader/player-coach on a risk core transaction platform (payments/branded checkout) who led major migrations from a monolithic stack to microservices, including API contract redesign and performance improvements (reported ~500ms latency reduction). Experienced running high-stakes production incidents (upgrade-related outage/degradation) end-to-end with RCA and rollout-process changes, and has accelerated delivery via documentation/tooling (audit sign-off cycle reduced from ~3 sprints to ~1).”

“Project lead who partners with PM and customers to gather requirements, adjust project plans, and deliver new functionality that drives customer satisfaction and revenue. Has experience building features end-to-end and presenting successful technical demos to engineering and management audiences; no stated experience with LLM/agentic systems.”

“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”

“Amazon engineering leader (15+ years) targeting Senior Manager/Director roles, with deep ownership of contact-center latency and reliability initiatives. Shipped a global production improvement cutting call latency 30–40% and led a complex Citrix SDK integration, including incident response and a backward-compatible rollout strategy to protect existing customers while enabling new features.”

“Backend engineer with Tesla experience who redesigned vehicle registration into a step-based, region-configured workflow across 4–5 microservices, enabling partial saves and reducing customer drop-off. Has hands-on experience scaling and securing Python/FastAPI APIs (OAuth2/JWT, CORS), migrating cold data from MySQL to MongoDB via Kubernetes CronJobs, and implementing RBAC/RLS with Supabase + Postgres.”

“Engineering/technology leader with IBM Cloud experience leading large-scale infrastructure modernization from classic architecture to a standardized VPC/next-generation DC platform. Reports major outcomes including cutting region launch time from ~18 months to ~3 months and reducing operating costs by ~80% via automation, modular undercloud services, and platform standardization, while scaling a globally distributed org with clear service ownership and accountability.”

“Internship at BlueFoxLabs building and deploying an AI/ML RAG system for a biopharma client on top of LibreChat, including an AWS Textract ingestion pipeline and PGVector retrieval deployed to AWS EKS. Demonstrated production-minded scalability work by moving from a vertically scaled EC2 setup to a horizontally scaling Kubernetes/EKS deployment, using CI/CD to safely incorporate requirement changes like tabular document data.”

“Operator with 20+ years experience and a business degree who led the build and deployment of a Medicaid fraud investigation product for Texas HHSC OIG, cutting investigation time from ~2 years to 90 days. Has government go-to-market experience and has raised a friends-and-family round for an earlier startup concept; now pivoting toward a healthcare-focused venture after a cofounder with core tech could not continue.”

“Aspiring founder exploring an AI automation startup focused on automating processes involved in building companies. Not yet developed specific use cases or raised capital, but describes a clear plan to validate ideas through use-case research, building a pilot, and testing with early customers; not familiar with the VC/accelerator landscape yet.”

“Fitbit engineer who has taken multiple projects from concept to release, including architecting a new warranty-evaluation system that achieved 100% accuracy and saved the company $6M. Interested in exploring startup ideas and emphasizes mission alignment and building strong cross-functional teams.”

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

“Backend/data engineer with Amazon supply-chain experience building production serverless Python services and ETL pipelines on AWS (Lambda, API Gateway, S3, RDS, Glue). Has modernized legacy SAS jobs into Python with rigorous parity testing and phased migrations, and has delivered major SQL performance gains (minutes down to seconds) through indexing and partitioning.”

“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”

“Built and shipped a real-time AI phone agent for small businesses that handles bookings/FAQs/messages using streaming ASR, an LLM with tool-calling, and TTS; deployed to production for multiple paying customers. Demonstrates strong applied LLM reliability practices (tool-first grounding, retrieval, hard-negative testing, and production monitoring) and experience orchestrating multi-step AI workflows with Airflow, Prefect, and AWS Step Functions.”

“Robotics software candidate with hands-on experience building controllers for an Autonomous Underwater Vehicle, including dual-PID control in Python with state-space modeling and a planned path to LQR. Developed ROS nodes for odometry-based localization, waypoint planning, and control command publishing, validated through a custom Gazebo/ROS simulation workflow with control-metric-driven testing. Also worked on F1Tenth simulation and scan-matching localization (PL-ICP), with additional cloud deployment experience using Docker/Kubernetes and CI/CD.”

“Backend/data engineer with healthcare/telehealth domain experience, building patient appointment and data-processing systems on AWS. Has delivered production microservices and ETL pipelines (Flask/Celery, Glue/PySpark) with strong reliability/observability practices (JWT, retries/timeouts, Sentry/CloudWatch) and modernization experience migrating SAS workflows to Python services, including a documented 10min→30sec SQL performance win.”

“Amazon Robotics engineer who deployed and scaled the Lumos camera-based package scanning work cell across EU sort centers (100+ work cells in 5+ sites), enabling remote launches via detailed runbooks and troubleshooting. Strong in AWS IoT/edge systems, with hands-on incident recovery (restored 34 down work cells) and secure multi-compute certificate provisioning using IoT Jobs, ACM/CA, and custom roles; delivered ~75% per-cell cost reduction vs Cognex-based approach.”

“JavaScript/TypeScript engineer from Ridgeline who built a retry feature for failed staging-to-production promotions with pre-promotion health checks. Brings a backend-scaling mindset to runtime performance work (metrics-first bottlenecking, Big-O analysis, async/parallelism, caching) and leverages Cursor/AI tooling to ramp quickly on large codebases.”

“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”