Vetted Python Professionals

Krishnamraju Penumatsa

Screened

Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines

Fort Worth, TX6y exp

“Data engineer currently at American Airlines who built and owned end-to-end flight operations and booking data pipelines (batch + real-time) using Azure Data Factory, Kafka, Spark/Databricks, Synapse, and Snowflake—processing hundreds of GBs/day. Strong focus on reliability and data quality (idempotency, checkpointing, retries, validation/alerts) and delivered near-real-time analytics powering Power BI dashboards; previously helped stand up an early-stage data platform at Sysco on AWS (Glue/S3/Redshift) with Airflow and Jenkins CI/CD.”

Vishal Kodakanchi

Screened

Director of AI Platforms & Architecture specializing in enterprise GenAI and AI Centers of Excellence

Mountain View, CA20y exp

“Software industry veteran (20 years) pursuing entrepreneurship; currently building an MVP software product aimed at solving specific finance and accounting problems for nano, micro, and small enterprises. Plans to run a metrics-driven pilot to validate demand before refining the product and raising capital; leveraging Google for Startups and exploring AWS for Startups.”

“Analytics professional with Bank of America experience analyzing the digital card replacement journey at scale, transforming 20M event records across 900K clients into actionable reporting and recommendations. Stands out for combining SQL/Python data engineering, customer journey analytics, and executive-facing storytelling strong enough to get senior leadership to adopt most of their proposed app improvements.”

“Analytics-focused candidate with experience owning end-to-end data projects across AI transcription, retail forecasting, and transportation revenue analytics. They combine strong SQL/Python pipeline skills with dashboarding and stakeholder alignment, citing measurable impact including 60% lower ETL latency, 18% better forecast accuracy, and 25% operational efficiency gains.”

“Platform/infrastructure engineer with hands-on ownership of Kubernetes, Terraform, VMware, and hybrid on-prem/AWS environments. Stands out for combining deep platform build/upgrade experience with strong incident response and reliability practices, including a Terraform redesign at H&R Block that reduced provisioning time by 40% and hybrid networking improvements that hardened Direct Connect failover.”

“Healthcare-focused data analyst with hands-on experience at Molina Healthcare building SQL and Python workflows for retention and churn analytics. They combined enrollment, CRM, and claims data into Power BI reporting, automated predictive churn analysis, and tied their work to measurable outcomes including faster processing, better reporting accuracy, and reduced churn.”

Neda Bokhari

Screened

Entry-level AI product and data professional specializing in workflow automation

San Francisco, CA1y exp

“Early-stage go-to-market candidate at Retroshift who has owned outreach across users, investors, and prospective clients in a zero-to-one environment. They’ve helped onboard 20+ alpha users and pushed the company into 3+ accelerator interview processes, showing strong traction-building ability through scrappy, multi-channel outbound.”

Udirno Chaudhuri

Screened

Mid-level Data Analyst and Product professional specializing in FinTech and AI applications

Santa Cruz, CA4y exp

“Payments/product-focused operator with hands-on experience owning complex bank connectivity deployments at Paystand, including a migration that raised connection success from under 50% to 79%. Also built a production-grade multi-agent document intelligence system on AWS Bedrock for structured enterprise document extraction, combining real-world fintech domain pain points with modern LLM architecture.”

Anthony Thanpoovong

Screened

Entry-level Software Engineer specializing in cloud, AI, and full-stack development

Toronto, Canada1y exp

“Backend/AI engineer with hands-on experience building LLM-powered data products and AI platform workflows, including a project that turns tabular datasets into graphs, summaries, and chat-based insights with 1-2 second latency. Also contributed at TELUS to a Sovereign AI Factory self-serve onboarding platform tied to 100+ NVIDIA H200 GPUs, giving them an interesting mix of applied LLM, platform, and infrastructure exposure.”

Yuchen Wang

Screened

Intern Software Engineer specializing in full-stack development and AI/ML

New York, NY1y exp

“Built and maintains an AI Finance Tracker end-to-end as a solo full-stack product owner, from Figma designs and React frontend to Flask APIs, Firestore, auth, deployment, and AI insights. Stands out for combining product instinct with pragmatic engineering decisions like pre-aggregating financial data to control LLM costs and adding OCR receipt scanning based on real user feedback.”

Rami Jaloudi

Screened

Senior Applications Engineer specializing in legal technology and eDiscovery

New York, NY16y exp

“Early-stage founder candidate exploring an AI-enabled legal tech startup focused on document intelligence, secure workflows, and enterprise automation. Brings a rare blend of technical architecture fluency and product/business thinking, with clear firsthand insight into legal and document-heavy operational pain points.”

“Salesforce-focused engineer with hands-on depth across Service Cloud, OmniScript/DataRaptor, LWC, Aura, and Apex. Particularly strong in building metadata-driven workflows that let operations teams change intake flows without developer tickets, while still making disciplined architecture decisions around when custom code is actually warranted.”

Michael Yeung

Screened

Mid-level Software Engineer specializing in FinTech trading platforms

San Francisco, CA4y exp

“Built and deployed internal trading tools at Wells Fargo that reduced manual production-support dependency for trader configuration workflows. Brings hands-on experience in financial systems, data quality, and production incident resolution, including building 400+ SQL validation rules and designing an internal RAG assistant for engineering documentation.”

“ML/AI engineer focused on taking LLM products from experiment to production, with hands-on ownership of a RAG-based customer support system that improved response quality by 35% and cut latency by 30%. Stands out for combining product impact with production rigor across retrieval tuning, safety guardrails, monitoring, and reusable Python/FastAPI services that accelerated adoption across teams.”

“Built and deployed an agentic RAG assistant in production to automate enterprise knowledge search and multi-step workflows with tool calling, tackling real-world issues like hallucinations, retrieval accuracy, and latency. Demonstrates strong LLMOps and orchestration depth (MLflow, Airflow, LangGraph/LangChain/LlamaIndex) plus a metrics-driven approach to agent testing/evaluation and cross-functional delivery with business stakeholders.”

“AI/LLM-focused builder with internship experience at Curated, where they owned a voice AI support deployment end-to-end and built a RAG-based internal knowledge assistant. They pair practical production instincts with measurable outcomes, including a 30% reduction in human-handled support tickets, a 20-point NPS improvement, and a 40% reduction in manual document search across five teams.”

Brendan Dwyer

Screened

Senior AI/ML Engineer specializing in GenAI and cloud platforms

Colorado Springs, CO10y exp

“ML/AI engineer with hands-on experience turning research-style RAG concepts into production underwriting systems at Prudential Financial. Built an internal document intelligence assistant end-to-end with strong monitoring, safety, and evaluation practices, driving a 38% faster review process and 31% better retrieval accuracy. Also improved platform engineering at VivSoft by standardizing Python-based ML deployment across 60+ models.”

Paavani Karuturi

Screened

Junior Backend and ML Engineer specializing in distributed systems and LLM infrastructure

San Jose, CA2y exp

“Backend engineer with strong ownership across authentication, API infrastructure, and AI-powered document workflows. They built and operated a production auth microservice supporting 10,000+ users with measurable latency and security improvements, and also shipped hackathon and applied-AI systems including legal document and medical document retrieval/Q&A products.”

Sai Sreenath Kalva

Screened

Mid-level Full-Stack Software Engineer specializing in AI and Healthcare IT

Rosemead, CA5y exp

“Full-stack engineer with strong AI architecture experience in regulated healthcare environments, including a HIPAA-compliant conversational reporting assistant for LA County Department of Public Health and clinical workflow features for Oracle Health/Cerner PowerChart. Stands out for combining LLM/RAG system design, healthcare compliance, and production-grade reliability practices across Azure, AWS, and Kubernetes.”

Sriram Degala

Screened

Senior AI/ML Engineer specializing in healthcare and finance AI

Dallas, TX4y exp

“Built production-grade medical AI systems at MD Anderson, including an end-to-end RAG chatbot used by clinical researchers for real-time drug interaction and trial literature queries. Stands out for combining healthcare domain knowledge with strong MLOps, evaluation, and safety practices, and for delivering measurable gains in latency, retrieval precision, and team adoption.”

“Software engineer with 4 years of experience spanning scalable backend systems, full-stack product development, and production LLM integrations in finance, insurance, and e-commerce contexts. They describe shipping an AI-powered internal financial analysis tool, improving document-review workflows by 40%, and driving a zero-to-one B2B SaaS subscription launch with cross-functional GTM alignment.”

“Healthcare analytics candidate with hands-on experience turning messy claims and clinical data into validated SQL/Python pipelines and Power BI dashboards. They have delivered measurable impact in revenue cycle operations, including 15-18% improvement in reimbursement accuracy and 40-45% reduction in manual reporting effort.”

“Full-stack engineer at an early-stage startup with hands-on production experience spanning Angular frontend features, backend safety checks for an image-generation workflow (OpenAI Safety), and AWS operations. Built CI/CD to ECS with GitHub Actions, implemented CloudWatch observability, and improved release reliability via Blue/Green deployments with automatic rollback.”

“Backend engineer in healthcare data systems who has owned production pipelines end-to-end, from ingesting patient and claims data to serving it through secure APIs. Brings a strong mix of Python, SQL, microservices, cloud deployment, and data reliability practices, with measurable performance gains and experience building resilient integrations with external data sources.”