Vetted Bash Professionals

Benjamin Agyekum

Screened

Senior Full-Stack Software Engineer specializing in AI-powered web and mobile applications

California, USA8y exp

“Backend/full-stack TypeScript engineer who has owned end-to-end, production-oriented systems including an AI property management platform (NestJS/Postgres/WebSockets on Google Cloud using Gemini Vision) and an AI logistics platform (Node/Redis queues/Postgres) focused on low-latency, correctness, and observability. Also designed a public GraphQL API and TypeScript SDK for education partners at StudyFetch, citing 40+ partner integrations in the first quarter.”

“Early major technical hire who helped build fintech startup Ugami from MVP to near Series A, while supporting bridge round and Series A fundraising with technical materials for leadership. Also grew from intern to lead engineer at a venture-backed product shop, giving him firsthand exposure to investor expectations, startup incubation, and practical AI opportunities with tight scope and strong unit economics.”

“Candidate is actively using AI-assisted development tools, including MCP server integrations with Copilot, to generate boilerplate test scripts, validate code standards, and handle package updates. They also have hands-on experience choosing different agents based on task requirements and serving as an admin for AI tool access.”

“Built and deployed a production RAG-based multilingual analytics assistant for healthcare operations, enabling non-technical teams to query claims/EHR and risk metrics with grounded explanations. Demonstrates strong end-to-end LLM system engineering (retrieval tuning, re-ranking, hallucination controls, verification layers) plus workflow orchestration (Airflow/Composer/Step Functions) and stakeholder-driven iteration via prototypes and dashboards.”

“Backend engineer who owned the API layer for an AI trust/analytics dashboard (trust scores, stability checks, public verification endpoints) using Python/FastAPI and Postgres. Has hands-on DevOps experience deploying FastAPI and Node.js services to AWS Kubernetes with GitHub Actions + ArgoCD GitOps, plus Kafka-based real-time event streaming and careful staged migration practices (shadow traffic/dual writes, rollback planning).”

“Built and deployed a production generative-AI copilot at Tungsten that automates invoice/form extraction template creation, reducing weeks of manual model-building work. Combines fine-tuned LLMs (PyTorch/HuggingFace) with OpenCV layout grounding to reduce hallucinations, and runs an end-to-end Kubeflow-based MLOps pipeline with drift monitoring, canary releases, and automated retraining.”

Mayank VYAS

Screened

Mid-level AI/ML Engineer specializing in LLM agents, RAG retrieval, and IoT ML systems

Tempe, AZ4y exp

“Built production LLM-driven products including a job-hunt AI (job ranking + resume optimization) and an InterviewAI agentic pipeline using LangChain. Focused on practical deployment concerns like securing OpenAI usage via rate limiting and tiered quotas, and demonstrates an applied approach to choosing models, retrieval methods (RAG), and prompting strategies.”

Srikar Tharala

Screened

Mid-level AI/ML Engineer specializing in Generative AI and RAG systems

Remote, USA4y exp

“Currently at ProShare and reports building an AI/LLM-powered system deployed to production, aimed at helping with status-related difficulties and reducing misunderstandings across transactions. Also cites prior collaboration at Porsche with marketing teams, focusing on translating marketing goals into technical requirements and communicating solutions clearly to non-technical stakeholders.”

Ram Abhinav Vedant Madabushi

Screened

Junior Full-Stack/AI Engineer specializing in web platforms and LLM applications

Palo Alto, CA2y exp

“Backend engineer from FoodSupply.ai who built and evolved a scalable restaurant/supplier product and order management platform using Node.js and REST APIs. Implemented a hybrid MySQL+MongoDB data architecture, optimized performance with Redis/Prisma, and led a phased migration with feature flags and a temporary sync layer to maintain data consistency. Strong focus on production security (OAuth2, RBAC, row-level security, AWS IAM) and reliability practices (testing with Pytest, Docker/AWS pipelines).”

“Software engineer with hands-on experience across platform modernization, production AI agents, and workflow automation. They led a monolith-to-microservices migration that increased deployment speed from weekly to daily, built a self-healing GPT-powered browser agent with an 85% autonomous recovery rate, and founded/ran ZapDash, where they hardened Kafka-based integrations against silent data loss.”

“Union College robotics graduate with hands-on ROS experience building an independent “waiter bot” that took spoken orders (Mozilla DeepSpeech), used OpenCV, and navigated via SLAM on a TurtleBot with LiDAR. Also led the Union College Robotics crew for four years and implemented PID control for micromouse maze robots; has additional software deployment experience with Dockerized FastAPI and CI/CD from coursework.”

“Built and deployed a production AI accessibility platform that turns chart and image-based graphs into real-time audio narratives for visually impaired users. Implemented a ResNet-based CV + OCR + NLP + TTS pipeline and improved performance through preprocessing, Redis caching, and Kubernetes autoscaling/rolling updates on AWS to handle traffic spikes with no downtime.”

Fernando de Cea Cotta

Screened

Senior Game Developer specializing in Unity and XR (AR/VR)

Spain9y exp

“Unity/C# developer with hands-on experience delivering performance-critical systems: built a multithreaded Addressables-based asset loading pipeline to handle thousands of animations and drastically cut loading screens. Also created a personal Unity Editor tool using the OpenAI API to detect code smells and generate prioritized remediation, and has shipped authoritative-server multiplayer for an arcade car game with prediction/interpolation, reconciliation, and robust live-network debugging.”

Revanth P

Screened

Mid-level DevOps Engineer specializing in AWS, Azure, Kubernetes, and GenAI infrastructure

Walnut Creek, CA4y exp

“Database/platform engineer with stronger hands-on experience in AWS and Azure than GCP, but able to speak credibly about cloud database architecture, automation, and reliability engineering. They led an on-prem MySQL to RDS/DynamoDB migration, built Terraform/Python-based zero-touch database operations, and described a performance incident where latency dropped from 2s to under 300ms while supporting 2x traffic.”

“Analytics professional with experience spanning infrastructure, energy, and digital engagement data. They have built SQL and Python workflows to turn messy operational data into trusted reporting assets, and led a wind turbine SCADA analysis that quantified roughly $1M in cumulative performance loss and translated findings into actionable Power BI dashboards.”

“Unity VR developer who has shipped Meta Quest titles both independently (handling art, engineering, marketing, and self-publishing) and on teams focused on architecture and code. Recently worked on a multi-user VR experience using haptic gloves and holopotation, solving Photon multiplayer bandwidth issues by compressing high-volume data and implementing custom sync strategies. Also experiments with integrating LLMs into Unity for NPC interaction and uses AI tools pragmatically for straightforward tasks.”

“Built and productionized an AI-assisted merchant onboarding automation workflow for Kort Payments, replacing slow manual underwriting document review with structured extraction, cross-document validation, and human-in-the-loop guardrails. Emphasizes reliability via scenario-based testing, repeatability checks, and deep observability (timestamped logs), plus incremental rollout with legacy fallback to prevent regressions.”

Erick Ortega

Screened

Junior Embedded & Computer Vision Engineer specializing in Edge AI and QA automation

Raleigh, NC2y exp

“Built a Meta-style AI smart glasses system emphasizing on-device privacy and low-latency processing, spanning ESP32-S3/FreeRTOS firmware through an NVIDIA Jetson Linux edge-AI pipeline in Python/Docker. Strong in real-time streaming optimization (zero-copy GDMA, deterministic scheduling), encrypted transmission (AES-256), and reliability via stress testing and robust error handling; currently building CI/CD automation tests using Playwright and computer vision.”

Emmanuel Sarpong

Screened

Mid-Level Full-Stack Developer specializing in React and ERP/NetSuite automation

Montreal, QC4y exp

“Frontend/full-stack product builder who led SiteSnap (field documentation platform) end-to-end, including UX design, React/TypeScript architecture, and deployment. Built a complex Report Builder editor handling thousands of media assets with strong performance practices (virtualization, lazy loading) and a quality pipeline (Storybook, Playwright, Vercel previews), and shipped a smart PDF report generator under a tight demo deadline with gradual rollout.”

Charmi Dharmendrakumar Parmar

Screened

Mid-Level Software Engineer specializing in full-stack and cloud-native systems

Alpharetta, GA4y exp

“Backend/full-stack engineer who owned a cloud-native, AWS-based microservices backend for an HRIS product used by ~10,000 users, including onboarding and workflow orchestration. Strong production focus on event-driven architecture, idempotency/retries, observability, and developer-friendly API design (OpenAPI, versioning, JWT), plus hands-on Selenium automation for resilient checkout-style flows.”

“Full-stack engineer who has owned both institutional and personal products end-to-end, including Rutgers' myCommunity platform used by 70,000+ students. Particularly strong in production systems, data synchronization, authentication, and third-party API integrations, with a pragmatic approach to shipping, observability, and UI modernization.”

“Built a production-grade clinical and insurance document AI system in a HIPAA/PHI-regulated environment, taking it from experimentation through Azure deployment, monitoring, and iterative improvement. Stands out for translating RAG/LLM research into reliable microservices with strong safety controls, drift monitoring, and human-in-the-loop workflows that cut manual review time by 60-70%.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”

“Cloud infrastructure/DevOps engineer focused on AWS/Azure production environments, with hands-on experience running EKS-based platforms, Terraform-driven IaC, and secure Jenkins/GitLab CI pipelines. Has led real-world migrations from EC2 to Kubernetes using blue/green cutovers and executed multi-AZ failover testing with documented same-day recovery and no data loss; does not have direct IBM Power/AIX ownership experience.”