Vetted Bash Professionals

“Full-stack engineer (4+ years) with Citigroup experience building a modular banking dashboard using React/TypeScript/Redux and a Java Spring Boot microservices backend (12+ services) integrated with Kafka. Strong in reliability/observability and cloud operations on AWS (EC2/S3/Lambda, CloudWatch, Prometheus, ELK, IaC with Terraform/CloudFormation), with quantified improvements in latency, development speed, and data pipeline correctness.”

“Infrastructure/platform engineer with hands-on ownership of on-prem OpenStack/VMware and Kubernetes clusters deployed via Kubespray, including OpenStack-integrated networking and Ceph-backed storage. Built a GitOps-style Terraform delivery model in GitLab with CI/CD and security scanning (SAST/DAST/Checkov), and operated a hybrid on-prem/AWS ecommerce architecture with PCI-segmented payment systems over site-to-site VPN.”

Somil Shah

Screened

Mid-level AI/ML Engineer specializing in generative AI, RAG platforms, and LLM agents

San Francisco, CA4y exp

“AI/LLM engineer who has shipped 10+ production applications, including InvestIQ on GCP—a production-grade RAG due-diligence engine that ethically scrapes web/PDF sources, builds a ChromaDB knowledge base, and delivers analyst-style dashboards plus a citation-backed chat copilot. Deep focus on reliability (evidence-only answers, hard citations, refusal gating), retrieval tuning, and orchestration (Airflow/Cloud Composer), plus multi-agent systems (CrewAI with 7 specialized finance agents).”

Vamshi Korra

Screened

Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices

Remote, USA5y exp

“Open-source React dashboard/visualization library maintainer focused on runtime performance and API clarity. Led a significant effort to eliminate severe render lag on large live-updating datasets through profiling-driven refactors (normalized state, memoized selectors) and locked improvements in with CI, linting, and documentation that reduced regressions and improved external contributor onboarding.”

Bala Venkateswarlu K

Screened

Mid-level Data Scientist specializing in Generative AI, NLP, and MLOps

USA5y exp

“Built and deployed an LLM-powered claims-document summarization system (insurance domain) that cut agent review time from 4–5 minutes to under 2 minutes and saved 1,200+ hours per quarter. Hands-on across orchestration and production infrastructure (Airflow retraining DAGs, Kubernetes, SageMaker endpoints, FastAPI) and recent RAG workflows using n8n + Pinecone, with a strong focus on reliability, cost, and explainability for non-technical stakeholders.”

Abi Olatunji

Screened

Senior DevSecOps/SRE Engineer specializing in secure AWS & Azure cloud platforms

Dallas, TX9y exp

“Senior production infrastructure/SRE-style engineer with deep IBM Power/AIX (7.2/7.3) ownership at scale (40+ LPARs) supporting SAP/Oracle, including live DLPAR changes and PowerHA clustering. Also brings modern cloud/DevOps experience—Azure DevOps CI/CD secured with Key Vault and Terraform-based Azure provisioning—bridging legacy enterprise platforms with cloud automation.”

Ioannis Gregos-Mourginakis

Screened

Mid-Level Software Engineer specializing in blockchain, data pipelines, and functional programming

Los Angeles, CA3y exp

“Built an LLM-powered production agent that scraped X.com data to categorize and profile accounts, deployed in Docker with automatic relaunch for high uptime. Interview details were limited, but the candidate does have hands-on experience shipping an AI automation workflow.”

“Entry-level software engineer who independently built an AI-powered feedback aggregation and analytics dashboard end-to-end using Cloudflare Workers, D1, and React. Stands out for combining serverless backend design, LLM-based categorization, and thoughtful UI/UX polish, with a practical approach to production debugging and data reliability.”

“Built a production, real-time clinical documentation system at HCA that converts doctor–patient conversations into structured clinical summaries using speech-to-text, LLM summarization, and RAG. Demonstrated measurable gains from medical-domain fine-tuning (clinical concept recall +18%, ROUGE-L 0.62 to 0.74) while meeting HIPAA constraints via PHI anonymization and encryption, and deployed via Docker/FastAPI with CI/CD and monitoring.”

“Built end-to-end product features spanning full-stack web development and LLM-powered systems in an early-stage startup environment. Notably shipped an AI financial assistant chatbot with agent routing, validation, fallback handling, and production monitoring, and also owned a scheduling system integrating Next.js, backend APIs, database design, and Google Calendar OAuth.”

“Yogesh is an AI/full-stack engineer from LangChain who says he was the sole developer and core maintainer of OpenSWE/OpenSpeed, an asynchronous coding agent in LangSmith Cloud that turns requests from Slack, Linear, and GitHub into reviewable PRs. He emphasizes production-grade agent infrastructure: event-driven workflow design, typed run states, observability, retries, and latency improvements via pre-warmed sandboxes.”

“Healthcare-focused LLM engineer who deployed a production triage and clinical knowledge retrieval assistant using RAG and LangGraph-orchestrated multi-agent workflows. Emphasizes clinical safety and compliance with robust hallucination controls, HIPAA/PHI protections (tokenization, encryption, audit logging, zero-retention), and human-in-the-loop escalation; reports a 75% latency reduction in a healthcare agent system.”

“Telecom (Verizon) AI/ML practitioner who built a production multimodal system that ingests messy customer issue reports (calls, chats, emails, screenshots, videos) and turns them into confidence-scored incident summaries with reproducible steps and evidence links. Also built KPI/alarm-to-ticket correlation to rank likely root-cause domains (RAN/Core/Transport), cutting triage from hours to minutes and improving MTTR.”

“Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.”

“Machine Learning Intern at Docsumo who delivered a customer-facing fraud-detection solution end-to-end: rebuilt the pipeline, deployed a Random Forest model, and shipped a Python/Flask microservice on AWS SageMaker. Drove measurable production impact (precision +30%, processing time cut in half, manual review -60%, customer satisfaction +15%) and demonstrated strong customer integration and live-incident response skills.”

“IBM engineer who built and deployed a production RAG-based LLM assistant using LangChain/FAISS with a fine-tuned LLaMA model, served via FastAPI microservices on Kubernetes, achieving 99%+ uptime. Demonstrates strong practical expertise in reducing hallucinations (semantic chunking + metadata-driven retrieval) and managing latency, plus mature MLOps practices (Airflow/dbt pipelines, MLflow tracking, monitoring, A/B and shadow deployments) and effective collaboration with non-technical stakeholders.”

“Robotics software candidate focused on ROS 2 simulation work: integrated a SolidWorks-designed truck + dual-trailer CAD model into ROS 2 Humble by building URDF/meshes, fixing coordinate/joint axis issues, adding ros2_control + Gazebo integration, and implementing teleop. Also built a Python P-controller node for autonomous pose navigation and has experience with common robotics/embedded communication protocols and Docker-based ROS environment setup.”

“Infrastructure engineer with hands-on ownership of a scaled IBM Power/AIX estate (AIX 7.x, VIOS, HMC; 2 frames/20+ LPARs) supporting critical middleware and database workloads, including live DLPAR changes and VIOS/SAN outage recovery. Also brings modern DevOps/IaC experience building GitHub Actions pipelines for Docker/Kubernetes deployments and provisioning AWS environments with Terraform (EKS/RDS/VPC/IAM) using modular, review-driven workflows.”

“Cloud/DevOps-focused engineer with production experience in Linux, AWS, Kubernetes, and cloud-native architectures. Has built GitHub Actions CI/CD pipelines for containerized Kubernetes deployments and implemented Terraform-based AWS infrastructure with modular design and remote state/locking (S3 + DynamoDB) plus PR/CI-driven change control.”

“Data engineer (~4 years) with full-stack delivery experience (Next.js App Router/TypeScript + React) building a real-time operations monitoring dashboard backed by Kafka and orchestrated data pipelines. Strong production focus: Airflow + CloudWatch monitoring, automated Python/SQL validation (99.5% accuracy), and CI/CD with Jenkins/Docker; has delivered measurable improvements in latency, pipeline reliability, and query performance (Postgres/Redshift).”

“Full-stack engineer with payments-domain experience from ACI Worldwide who shipped an end-to-end MFA system for payment workflows (React/TypeScript + backend APIs + Postgres), then owned it in production with logging/monitoring and client adoption tracking. Also improved checkout responsiveness across Apple Pay/PayPal flows via React performance profiling, component refactors, and state/network optimizations.”

“Data engineer focused on sales/marketing analytics pipelines, owning ingestion from CRMs/ad platforms through warehouse serving and dashboards at ~hundreds of thousands of records/day. Built reliability-focused systems including dbt/SQL/Python data quality gates with alerting, a resilient web-scraping pipeline (retries/backoff, anti-bot tactics, schema-change detection, backfills), and a versioned internal REST API with caching and strong developer usability.”

HASHIM YAQUB

Screened

Staff Unity XR Software Engineer specializing in VR surgical training and haptics

Bath, UK12y exp

“Unity/VR developer with hands-on experience integrating Pupil Labs eye tracking on HTC Vive to make VR interactions and diegetic UI feel more natural, including building calibration directly into the app for different users. Developed multi-user applications at Fundamental VR using Photon PUN 2 for cross-platform networking, and leverages AI tools for debugging/optimization and GitHub Actions CI/CD pipeline troubleshooting.”

Bhakti Patel

Screened

Senior Full-Stack Software Engineer specializing in .NET, Python, and cloud-native systems

Worcester, MA11y exp

“Full-stack engineer who owned an end-to-end production feature for a Piraeus Bank stock exchange module, spanning React/TypeScript, backend services, and cloud operations with Docker + CI/CD, delivering reported 90% faster API responses and improved uptime. Also built a Smartwound research MVP on AWS, creating a Python image-processing/scoring pipeline to ship despite unclear image-analysis specs.”