Vetted Python Professionals

“LLMOps-focused technical leader who took an LLM use case from prototype to production for a non-technical customer by combining trust-building and structured enablement with a robust AWS/Kubernetes-based MLOps stack. Built observability and rollback mechanisms (Grafana + MLflow) to troubleshoot in real time, and scaled delivery by hiring a 5-person team while partnering with sales to manage expectations and drive adoption across departments.”

“Player-coach engineering leader focused on scalable data security scanning and risk detection in hybrid cloud, owning architecture and core implementation of an incremental/parallel DSPM scanning engine. Shipped production improvements including 60% lower scan latency and 30% fewer false positives, with strong emphasis on correctness under concurrency, multi-tenant observability (SLOs/burn-rate alerts), and disciplined rollout practices (feature flags, shadow scans, canaries).”

Parth Vadera

Screened

Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps

Tracy, CA11y exp

“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”

Dennis Noto

Screened

Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization

Denver Metro Area36y exp

“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”

Sujit Singh

Screened

Engineering Director specializing in backend & data platforms for enterprise SaaS and cybersecurity

San Jose, CA21y exp

“Backend/data engineering player-coach on a UEBA cloud security analytics platform who standardized MLOps and detection development for 180+ detections, cutting ship time from 6–7 weeks to ~3 weeks while reducing false positives. Proven at operating large-scale streaming + Spark systems (200K+ events/sec, 100+ TB/day), driving major reliability/cost improvements, and leading incident response and team execution through GA.”

“Senior engineering executive-level leader with deep hands-on systems expertise across Amazon devices, Alexa, Echo, and FireTV/VegaOS. Unusually combines VP-level org leadership at 120+ scale with direct production debugging and architecture ownership, including hybrid edge-AI/cloud systems, partner platforms for 9000+ apps, and shipping long-horizon platform bets under aggressive release cadences.”

“Software engineer with experience across early-stage startups and production full-stack systems, including migration work from a Go monolith to a Node.js backend and a clinical research application deployed on Kubernetes in AWS. Has worked across Go, Python, JavaScript/TypeScript, React, SQL databases, and B2B SaaS data-streaming products.”

“Full-stack engineer with strong startup experience across small distributed teams, owning everything from React UIs to Go services and Python data pipelines. He stands out for designing stable APIs and data models in ambiguous compliance-heavy environments, with measurable impact including a 38% reduction in manual cleanup and a 27% drop in customer-visible incidents. He has also worked deeply in B2B SaaS at Ashby, supporting mission-critical recruiting workflows where data correctness, permissions, and integration stability were essential.”

Kusumita Dasgupta

Screened

Director-level Engineering Leader specializing in data platforms, cloud systems, and LLM products

United States22y exp

“Engineering leader/player-coach with recent hands-on work delivering an agentic AI MVP on Amazon Bedrock (conversational UI + supervisor agent routing between internal knowledge and external sources). Previously drove large-scale data platform cost optimization at Twitter, saving ~$3M–$5M annually, and has owned production incidents end-to-end with a focus on analytics/monitoring improvements and team coaching.”

Sanket Patel

Screened

Director-level Front-End Engineering Leader specializing in scalable web and mobile apps

Palo Alto, CA17y exp

“Amazon engineer/leader who drove a major modernization of the AWS Database Migration Service Console, migrating a monolithic UI to a micro-frontend architecture while improving performance, reliability, and engineering standards. Operates as a player-coach (80/20 hands-on/management), with demonstrated incident ownership and process improvements across Amazon and Walmart Labs.”

Tina Bai

Screened

Executive operator-founder specializing in GTM, revenue strategy, and AI-native commercial operations

New York, NY10y exp

“Operator with Deloitte consulting experience supporting PE/VC-backed portfolio companies and current experience inside a VC-funded Series C scale-up. Building a bootstrapped D2C women’s telehealth brand (Petty Pills) with two initial SKUs, deployed tech stack, and white-labeled clinical/compliance infrastructure, leveraging AI tooling to keep operations lean while focusing on full-time operator roles.”

Chinedu Enwere

Screened

Mid Software Engineer specializing in distributed backend systems

Redmond, WA4y exp

“Engineering candidate deeply embedded in AI-native development, currently using tools like Cursor and Claude Code to generate most of their code and building internal agents for on-call monitoring, anomaly detection, and automated incident mitigation. Particularly interesting for teams exploring AI-first engineering workflows, multi-agent development setups, and operational automation at scale.”

“Senior engineering leader with a rare blend of deep platform/infrastructure expertise and large-scale people leadership, spanning hands-on cloud-native architecture through management of globally distributed organizations of up to roughly 180 engineers. Particularly strong in Kubernetes platform modernization, reliability engineering, and scaling high-throughput SaaS systems while aligning platform investments to customer and business outcomes.”

Xun He

Screened

Staff Software Engineer specializing in backend systems and security engineering

25y exp

“Senior backend/infrastructure engineer with experience at Microsoft, DocuSign, Pinterest, and Harness, focused on security and developer productivity systems. Stands out for building Pinterest's first vulnerability management platform from scratch for a 100,000-EC2 production environment and driving major performance gains, while also delivering CI/Docker infrastructure and Python test intelligence features shaped by customer demand.”

“Robotics student who built a fully autonomous "Pacman" robot car using ROS 2, integrating LiDAR/IMU sensing with localization, autonomous driving, and a custom RRT + A* planner. Demonstrated practical embedded optimization on an RP2040 by balancing replanning frequency with safety via rapid collision checks.”

“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”

“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”

“Engineering/product leader with repeated experience defining roadmaps and delivering platform migrations across SaaS and enterprise contexts. Scaled an education system from two districts to 2M+ students statewide, and led an Elasticsearch-based architecture for an internal Disney product serving ~100K employees. Known for rigorous execution (RAID/OKRs/sprints), strong stakeholder communication (weekly AI summaries), and empowering teams via end-to-end ownership and customer-connected development.”

“Game UI engineer with shipped experience on Paladins (Unreal Engine 3/C++), including an in-game store with automated grid-based recommendation layout and an inventory UI built for PC/PlayStation/Xbox/Switch. Emphasizes production readiness through clean separation of UI/data, strong documentation for engineering and content workflows, and memory-conscious UI patterns (pooled entries/paged navigation) for constrained platforms like Switch.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”

Jun Ouyang

Screened

Principal Software Engineer / Tech Lead specializing in distributed systems, payments, and reliability

San Francisco, CA20y exp

“Backend engineer with DoorDash experience building production-critical systems spanning LLM-based real-time safety moderation (SendBird callbacks + ChatGPT risk scoring with automated actions) and large-scale payments data pipelines (Kafka to CockroachDB with aggregation APIs). Also led cross-team reliability work to standardize SLOs and drove an incident redesign from batch pull to real-time push callbacks to eliminate critical-event latency.”

Brett Potter

Screened

Director-level Blockchain Engineer specializing in smart contracts and Web3 infrastructure

Miami, FL15y exp

“Technical leader with startup and venture experience who recently had a modest exit from a crypto protocol called Buck. Previously served as Technology Director at Launch Code Capital and has worked across multiple startups, bringing both operator and VC-side perspective.”

“Engineering leader with a mix of large-scale platform experience at Microsoft and product/customer-facing work across GM, Panasonic, Acuity, and other environments. Stands out for combining people leadership with hands-on depth in accessibility, web performance at 120M+ MAU scale, and cross-functional delivery spanning enterprise permissions, e-commerce, AI, and automotive systems.”

Vinay Ramrupe

Screened

Mid-level AI/ML Engineer specializing in LLM and enterprise generative AI

San Francisco, CA5y exp

“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”