Vetted Artificial Intelligence Professionals

“Founding engineer for an AI product (“world’s first funny AI”) who designed and implemented the full-stack architecture (React/TypeScript + Node) and migrated production from Vercel to AWS. Shipped a Lambda-based image pipeline that eliminated lag/missing images and brought page load times to under a second, and has hands-on experience integrating multiple LLM providers (OpenAI, Claude, Gemini, Grok) with structured-output and self-check reliability techniques.”

Allan Farinas

Screened

Senior Full-Stack Software Engineer specializing in Python and AWS

West Covina, CA11y exp

“Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.”

Bassam Amrou

Screened

Director-level Digital Solutions & IT Transformation Leader specializing in enterprise innovation

Plano, TX12y exp

“Entrepreneurial operator with experience creating business plans and securing venture capital to accelerate a go-to-market strategy. Demonstrates a structured approach to new ventures: framing opportunities, validating/de-risking via market/competitive/external analysis and financial modeling, then building governance, sponsorship, and an execution plan with the right team.”

Sai Charan Kolla

Screened

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS

TX, USA5y exp

“LLM engineer who built a production document intelligence/RAG pipeline to extract structured data from thousands of unstructured PDFs, cutting manual review time by 60%. Experienced with LangChain and Airflow orchestration plus rigorous evaluation (labeled datasets, prompt testing, HITL review, monitoring) to improve accuracy and reduce hallucinations while partnering closely with non-technical operations stakeholders.”

Edgar GranadosOsegueda

Screened

Mid-level Robotics Researcher specializing in kinodynamic motion planning

Rutgers, USA7y exp

“Robotics software engineer focused on real-time estimation/control and motion replanning, currently integrating a factor-graph-based estimation/control stack with sampling-based replanning in a ROS environment validated on both MuSHR hardware and MuJoCo simulation. Strong in distributed-system debugging (rosbags/logging, controlled test scenarios) and ROS performance patterns (nodelets, TF/TF2), with prior multi-robot experience from SSL RoboCup using custom UDP protocols.”

“Backend/data engineer with experience at Citi and Elevance Health, building end-to-end pipelines and data services in regulated, high-volume environments. They combine Python, SQL, .NET, Azure Functions, and strong observability/reliability patterns to improve processing speed, reduce manual effort, and maintain high uptime across financial and healthcare data platforms.”

“Repeat founder and active VC with over 3 years of experience running a fund and syndicate. Currently exploring an agentic deal flow CRM for venture funds, with early components already built and a clear plan to dogfood it and recruit other VCs for validation.”

Amaan Elahi

Screened

Mid-level Software Engineer specializing in backend, AI, and full-stack systems

New York, NY5y exp

“Built and shipped production LLM agents including an internal RAG-based compliance classification system at SAIL (FastAPI/Redis/Docker) designed to handle real failure modes and scale to ~10k LLM calls/hour, achieving ~93% pipeline accuracy with reduced hallucination risk via multi-model orchestration and strict grounding. Also architected “Elara,” a state-machine-driven conversational appointment booking agent using structured JSON outputs and backend function execution for reliability, and has experience normalizing messy OTA/PMS data at RateGain.”

Pahuldeep Singh

Screened

Senior Full-Stack Developer specializing in scalable web platforms and automation

Remote6y exp

“Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.”

“Built Bargain Bricks end-to-end as a solo creator, handling product ideation, design, backend, APIs, website, and native iOS/Android apps. They actively maintain and iterate on the product, which has over 1,000 downloads, and have improved conversion through UI changes that surfaced the best deal above the fold.”

“Built a Flask-based web application for NCAA Men's gymnastics and also worked on a survey-question collection and normalization project for UC Berkeley's Cameron Institute. Shows a clear reliability mindset through validation, testing, logging, and error handling, and is comfortable turning ambiguous, messy data workflows into stable applications.”

Anirban Ghosh

Screened

Mid-level Machine Learning Engineer specializing in data science and cloud systems

Seattle, WA4y exp

“ML engineer who independently pitched and built a recommendation engine at Danske Bank in a legacy fintech environment, creating compliant data pipelines and deployment infrastructure from scratch and delivering a 62% engagement lift with 70%+ advisor adoption. Also worked at AWS on classification and GenAI-powered reporting systems, with strengths spanning production ML, platform setup, monitoring, and research-to-production optimization.”

Sergio Nunez

Screened

Senior Unity Engineer specializing in XR, mobile, and AI avatar experiences

Los Angeles, CA9y exp

“Unity/C# game engineer from Genies who built the avatar wearable customization system for Silver Studio and supported AI companion features through client-side LLM integrations. Stands out for combining clean architecture, analytics-driven product thinking, and practical optimization work across latency, AI cost controls, and mobile performance.”

Alexander Awn

Screened

Director-level UX leader specializing in automotive and inclusive design

Farmington Hills, MI21y exp

“Design and UX leader in automotive and service design who helped ship a novel 2015 Ford Mustang app featuring early augmented reality/visual search capabilities. Combines hands-on product design with strong mixed-methods research and has influenced major business decisions, including research that reportedly saved a client $8M by stopping a poor market launch.”

“Former Societe Generale investment banking/markets professional turned startup operator who became the first employee at Two Dots and helped scale it from prototype to $12M ARR. Combines executive-level financial analysis, AI product understanding, and hands-on GTM/customer execution, with a standout example of building a backtest-led enterprise sales motion that pushed conversion above 90% and helped win major property management customers.”

“Serial venture builder/operator across ad tech, media delivery, search engines, international content management, and ecommerce; has raised up to $150M and been involved in 8 acquisitions or IP-acquisition events. Known for refactoring/re-engineering smaller or troubled platforms into higher-value businesses, including building yield-management algorithms and a Kafka-like system to improve ad delivery profitability.”

“Software engineer with hands-on embedded/robotics coursework experience (Arduino sensor integration and input handling built from scratch without external libraries) and strong DevOps/engineering productivity impact at work, including leading a CI/CD enhancement that runs only impacted tests to catch issues before PR approval.”

“Software engineer with experience building a Vue.js/TypeScript internal component library (with Jest testing standards) and improving JS runtime performance via profiling, code splitting, and lazy loading. Also led documentation and community support for a Python ML utility library, diagnosing metric-calculation bugs for imbalanced datasets and driving large reductions in support inquiries through targeted docs, tests, and rapid hotfixes in a startup environment.”

“Serial entrepreneur who built Verb Technology from a garage startup to a Nasdaq IPO, raising multiple rounds of capital along the way. Invented interactive live streaming technology that was acquired by Amazon and demonstrated rapid product/market response during COVID by prototyping and launching a solution for users while tightly managing AWS costs.”

“Infrastructure-leaning engineer who has built real-time ML systems end-to-end: a Jetson-deployed adaptive Whisper ASR service (Flask + WebSockets, React/TS UI) and a high-throughput Postgres schema for live transcription. Also delivered customer-facing AI billing/OCR improvements for a dental startup (Dentite), boosting OCR performance by 38%, and has experience instrumenting open-source ML deployment stacks to add infrastructure visibility.”

Edward Robinson-Adams

Screened

Executive cybersecurity and AI leader, CEO/co-founder specializing in enterprise SaaS and strategy

Boston, MA35y exp

“Operator who took a seed-funded university spin-off in cybersecurity from zero revenue and heavy losses to profitability and industry leadership, while building the full internal ops stack (HR/payroll/benefits/401k) and the initial GTM engine (Salesforce/HubSpot, SPIN + MEDPICC). Personally led fundraising across 30+ VC pitches, raising $11.2M total and delivering $98M returned to investors to date, with additional upside from a subsequent spin-off.”

Ajay Madhusudhan Thumala

Screened

Junior Software Engineer specializing in data engineering and LLM applications

Irvine, CA1y exp

“Computer science engineer and master’s graduate who independently built a mechatronics-heavy capstone prototype: a smartphone concept for deafblind users using micro-actuator arrays for braille reading. Also has platform engineering experience at Quantiphi, deploying webhooks to Kubernetes and implementing GitOps-based CI/CD using AWS CodeCommit/CodeBuild and ECR.”

Nikhil Soni

Screened

Junior AI/ML Engineer specializing in LLM systems and retrieval-augmented generation

New York, NY2y exp

“Built and deployed a production LLM-powered market intelligence and decision-support platform for noisy, real-time financial data, using a high-throughput embedding + vector DB RAG architecture to reduce hallucinations while keeping latency and cost low. Operated it at scale with GPU-backed inference (continuous batching/quantization), FastAPI on Kubernetes, and Airflow-orchestrated ingestion/embedding/retraining workflows, with strong schema-based reliability and monitoring.”