Vetted Python Professionals

“Backend/platform engineer who has owned real-time reporting and streaming analytics systems end-to-end, combining FastAPI/Postgres APIs with Kafka consumers, Celery background jobs, and Redis caching. Strong DevOps/GitOps experience deploying Python/Node microservices to AWS EKS with Helm, ArgoCD/FluxCD, and CI pipelines, and has supported phased on-prem to AWS migrations using Terraform and traffic cutovers.”

“Software development manager who led development of the open-source AI agents framework Strands (for Amazon Bedrock), which launched mid-year and is used as a primary agent-development framework at Amazon and externally. Owned the Strands SDK end-to-end, drove adoption through stakeholder management and agile execution, and led a JavaScript-to-TypeScript migration to improve type safety and maintainability.”

“Engineering leader who drove Lightroom Mobile’s roadmap at Adobe by enforcing reuse of Photoshop imaging tech to deliver RAW, non-destructive mobile editing with full Creative Cloud compatibility. In startup environments, has repeatedly scaled and professionalized engineering orgs (career ladders, evaluation systems, delivery process) and led high-stakes cloud/platform transformations—migrating off Heroku and consolidating fragmented AWS/GCP usage into a single GCP platform—improving reliability, deploy speed, and cutting cloud costs by 20%+.”

Danny Anop

Screened

Senior Full-Stack Engineer specializing in SaaS, e-commerce, and frontend platforms

Bellevue, WA10y exp

“Frontend-leaning full-stack engineer who has built a multi-tenant AI-powered widget and admin dashboard platform used across 40+ merchant websites. Strong in TypeScript/Next.js/GraphQL systems design, reusable platform primitives, and cross-layer debugging, with a clear track record of shipping scalable product experiences under ambiguity.”

Kevin Wang

Screened

Senior Software Engineer specializing in cloud infrastructure and distributed systems

Adams, MA8y exp

“Amazon engineer focused on productionizing LLM-powered developer workflows, including code assistance, debugging automation, and internal AI tooling. Stands out for combining hands-on ML systems work with strong platform engineering, including an orchestration engine that reportedly saved about $10K/day and reduced a manual workflow from 12 hours to under a second.”

Christopher Sipola

Screened

Senior Machine Learning Engineer specializing in LLMs and recommendation systems

New York, NY11y exp

“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”

“LLM/agent engineer who built a production code-generation agent at Corvic AI that lets non-technical users query CSV/tabular data in natural language by generating and executing Python. Focused on making LLM systems reliable and scalable via schema-aware validation, sandboxed execution-feedback retries, prompt caching/embeddings, async execution, and high-throughput data processing with Polars; also partnered with Adobe product/marketing to ship brand-aligned AI content generation for email and push notifications.”

SHIVA SANDY

Screened

Executive CTO/CIO specializing in FinTech, cloud transformation, and cybersecurity

Walnut Creek, CA27y exp

“Banking/credit-union technology executive (CTO/CTIO) who has led modernization and product delivery through major change, including a post-merger roadmap that helped grow a credit union from $600M to $1.5B in 3 years. Hands-on leader who drove cloud microservices/API architecture, introduced CI/CD, and accelerated releases from quarterly to weekly while scaling teams and operating effectively with distributed/remote orgs.”

Somya Upadhyay

Screened

Senior Software Engineer specializing in cloud infrastructure and large-scale data pipelines

Bellevue, USA9y exp

“Backend engineer on Amazon’s Geospatial Data team (Amazon Maps) who built a real-time road-layer service ingesting third-party and internal signals to deliver road closures/traffic overlays to delivery drivers on a ~3-minute cadence while minimizing mobile data egress. Demonstrates strong production reliability skills (rate limiting, idempotency, cache stampede prevention) and security depth (IAM, RBAC, tenant row-level security), plus careful handling of edge cases like manual override protection against automated feed overwrites.”

“Early-stage investor/sourcer with experience at Insight Partners and M13 who combines thesis-driven outbound with deep ecosystem presence to generate proprietary founder relationships. Particularly strong in generative AI, creative tooling, and commerce tech, with added credibility from Gold House Ventures fellowship, angel investing communities, and a fractional fundraising advisory practice that has helped founders close rounds.”

Franklin Dickinson

Screened

Senior Data Scientist specializing in product analytics and applied AI

New York, NY9y exp

“Product data scientist at Meta who also built Fogo, a personal finance app, as a solo developer with a React/FastAPI/Postgres stack and sophisticated LLM evaluation infrastructure. Particularly strong in AI backend quality systems, experimentation, and production decision-making around model cost, latency, and reliability.”

“Clean energy founder (Ishan "Summer") who built an energy storage/battery materials venture in 2022 focused on data centers and factories, raising $10M split between venture capital and government funding. Demonstrates end-to-end venture execution: multi-year market observation, team formation, customer/market validation, research collaboration, prototyping, and channel-partner-led go-to-market.”

“Hands-on engineering leader with early-stage startup experience who balances coding with executive alignment and delegation. Has delivered offline-capable SaaS mobile demos under tight timelines, built monetization-ready mobile architectures (dynamic cloud assets + in-app purchases), and increased product velocity via component-based game architecture plus stakeholder self-serve tooling.”

“Founder-sourcing and pipeline operator with energy/sustainability network who has sourced and built multi-touch relationships with founders (including an SF-based founder building an AI platform for data-center permitting/financing/offtake). Uses a structured discovery and tracking process, provides value through insights and introductions, and produces partner-ready summaries and recommendations to drive go/no-go decisions.”

“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”

“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”

Gabriel Aguiar

Screened

Entry-Level Software Engineer specializing in AWS cloud infrastructure and distributed systems

Arlington, VA1y exp

“Robotics software engineer with hands-on ROS 2 experience who helped build an autonomous 5-DOF robotic arm that plays Backgammon, owning perception (OpenCV) and game-logic while adding robustness features like lighting tolerance and auto-calibration. Also worked on a Raspberry Pi/LiDAR car project, improving mapping accuracy through data-logged calibration and contributing to multi-robot collision-avoidance coordination via a server-based pub/sub system.”

“Entrepreneur building an AI-driven small molecule biotech startup who has already raised $5M from major venture capital investors. Brings 3 years of fundraising experience and a thoughtful approach to aligning investors with different risk profiles across financing stages, paired with strong conviction around founding high-risk, high-upside companies.”

“Research-oriented ML engineer/scientist with deep experience applying generative models, adaptive optimization, and HPC infrastructure to complex physics analyses. Built reusable Python-based tools that replaced expensive Monte Carlo workflows, integrated across HTCondor/SLURM environments, and reduced analysis timelines by 2x while supporting broader team adoption and training.”

Muneendra M

Screened

Mid-level Software Engineer specializing in event-driven backend and AI-enabled systems

San Francisco, CA4y exp

“Full-stack engineer at Stripe who owned a webhook monitoring and retry platform end-to-end, spanning backend services, React dashboards, and production operations. Stands out for combining strong distributed-systems judgment with product polish, including a reported 31% improvement in webhook delivery reliability and UI improvements that reduced support burden.”

“IBM Power/AIX infrastructure engineer who has owned large-scale Power9/AIX 7.x estates across primary/DR (VIOS/HMC/vHMC) and has deep hands-on experience with DLPAR, shared processor pool governance, and PowerHA recovery. Also brings modern DevOps/IaC capability—built Azure DevOps/GitHub CI/CD for Terraform + Kubernetes/Helm with strong security controls and resolved a production Terraform state-lock failure by redesigning backend locking and pipeline concurrency.”