Vetted Python Professionals

“Backend engineer with end-to-end ownership of scientific and AI-powered systems, including neuron imaging pipelines at Monell Chemical Senses Center and an LLM-based structured information extraction platform for Wharton and PSG. Stands out for turning messy, compute-heavy workflows into reliable production backends with measurable impact, including saving researchers over 50 hours per week.”

“Enterprise-focused SDR candidate with experience prospecting into some of the largest companies in the world using multi-channel outbound, personalized trigger-based messaging, and multithreaded stakeholder outreach. They report never missing quota, worked toward quarterly goals of 20 meetings and $1M in pipeline, and are especially motivated by founding SDR environments where they can help build the pipeline engine from scratch.”

Xingyu Chen

Screened

Junior Machine Learning Engineer specializing in generative AI and computer vision

Atlanta, GA1y exp

“Built production AI features for image editing and object removal, including an agent that guides users to the right pipeline, validates inputs, refines prompts, and routes requests to GPU-backed generation services. Brings hands-on experience across multimodal control, generative model optimization, and post-launch iteration driven by failure analysis and user feedback.”

“Built both traditional data infrastructure and LLM-powered product workflows, spanning a Python/SQL ETL deployment at Amazon and an adaptive learning system for their DataLingo platform. Particularly interesting for roles at the intersection of data engineering, applied AI, and customer-facing product delivery, with hands-on experience stabilizing probabilistic LLM systems in production.”

Chaithanya Konda

Screened

Mid-level Data Engineer specializing in multi-cloud analytics platforms

Waltham, MA6y exp

“Data engineer with hands-on GCP platform experience spanning BigQuery, Cloud SQL, Dataflow, and Cloud Composer, including both production operations and cloud migration work. They led a migration from legacy SQL Server/Oracle systems to a cloud-native BigQuery architecture and cite measurable impact: processing reduced from hours to minutes, query latency improved 60%+, and ingestion time improved 40%.”

“Software engineer with practical, day-to-day experience embedding AI into development workflows across coding, testing, code review, and AWS data pipelines. Uses tools like Claude, Cline, JUnit, Mockito, and Amazon Bedrock, and stands out for having a realistic, mature view of agent limitations, hallucinations, and the need for strong prompting and human validation.”

“Senior software engineer candidate who uses AI and multi-agent workflows thoughtfully to speed up development while preserving engineering rigor for production-critical decisions. Stands out for a clear risk-based framework: leveraging agents for boilerplate, refactoring, testing, and debugging, while relying on fundamentals, metrics, and human review for system design and scalability.”

Akhilesh Patil

Screened

Junior AI/ML Engineer specializing in FinTech and generative AI

Remote, USA2y exp

“Built an end-to-end AI bug triage dashboard that combined React/TypeScript, FastAPI, Postgres, and classical ML to reduce manual engineering triage work by about 40%. Stands out for pragmatic, product-minded AI engineering: choosing interpretable models when they were sufficient, designing human-in-the-loop UX for trust, and separately building an agentic RAG project with vector search, Neo4j knowledge graphs, and reranking.”

Ethan Hu

Screened

Entry-level Software Engineer specializing in full-stack and embedded systems

Seattle, WA1y exp

“Backend/full-stack engineer on Qualtrics' Online Samples team working on audience sampling systems and APIs used by researchers. They have hands-on ownership of TypeScript/React/Express services, emphasize multi-layer testing and production observability with Splunk/VictorOps, and have built APIs for both internal and external developers.”

“Built and deployed PIKA, an internal multi-agent platform for FDA-regulated software development, owning it from concept through production. The candidate combines strong full-stack engineering with rigorous LLM orchestration, human-in-the-loop controls, and production eval systems, delivering measurable impact: 3x more design issues caught, ~90% fewer false positives, and ~40% efficiency gains on documentation-heavy workflows.”

“Solutions engineer with recent experience in semiconductor and manufacturing SaaS, spanning pre-sales demos, SOW/POC authoring, on-site deployments, and production integrations. Particularly notable for bridging factory-floor equipment, on-prem Java applications, and Azure cloud systems, while also operating in highly regulated NIST 800-53 defense environments.”

“Software engineer with experience spanning early-stage startup architecture and large-scale Amazon product development. They’ve driven search and data-platform decisions in a 20-person startup, built full-stack React/Python tools that automate internal workflows, and shipped marketplace expansion and personalization features impacting 200k sellers and millions of end users.”

“Full-stack engineer with experience spanning a lean startup at AppLovin and production financial systems at Vanguard. They’ve built core user-facing platforms from scratch, including a B2B advertiser/publisher dashboard and a resilient client onboarding system using Spring Boot, NestJS, Postgres, Kafka, Redis, and AWS. Particularly strong in ambiguous environments where they work directly with stakeholders and own delivery end to end.”

“Built and owned an LLM support copilot at Stripe focused on improving agent ticket resolution. Designed the backend and ML system end to end, using RAG, Redis caching, hybrid vector search, and LoRA fine-tuning to achieve 40% lower latency and 22% higher response accuracy, with continuous quality monitoring via Ragas and related evaluation frameworks.”

Jahnavi Rao

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech

USA5y exp

“Backend engineer currently at Bank of America with experience in scalable backend services, microservices, and event-driven systems. Stands out for using AI pragmatically as a productivity accelerator while maintaining strong engineering judgment around reliability, security, and production validation, and shows strong architectural intuition for multi-agent workflows through a distributed-systems lens.”

Josh Rhoades

Screened

Executive Technology Leader (CTO) specializing in AI-enabled SaaS and regulated platforms

Los Angeles, CA30y exp

“Senior engineering leader with experience at Disney and BlackLine who drives business-aligned technology roadmaps through deep Product/Engineering partnership (two-in-a-box) and pragmatic prioritization frameworks. Has led major modernization initiatives—private-to-public cloud migration to GCP with multi-cloud evolution, data-layer performance improvements (Mongo/Redis, caching/query optimization), and tooling upgrades (VSS to GitHub)—while scaling teams with strong quality and accountability culture.”

Kevin Hoffman

Screened

Director-level product and engineering leader specializing in distributed systems and cloud platforms

Windsor, CT16y exp

“Former CTO and co-founder of Cosmonic who led technology vision, roadmap, and team building while also serving as the technical lead in investor and VC meetings. Has hands-on experience supporting seed and Series A rounds, plus strategic exposure to later-stage fundraising at Synadia, combining startup-building depth with a pragmatic view of risk and business viability.”

“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.”

“Player Experience developer on Madden who shipped player-facing Weekly Recap and Halftime Show flows built in visual scripting, including a custom solution to keep full-screen UI persistent across level loads with strong logging and failsafes. Also builds networked UE co-op ARPG systems (talent trees, combat/animation, leveling/stats, AI, dynamic spawning) and has a track record of refactoring shared UI/banner logic into scalable prefabs to reduce bugs and improve team workflow.”