Vetted Unit Testing Professionals

“Java full-stack developer who has owned data-intensive, customer-facing and internal web products end-to-end (React/Angular + Spring Boot), including CI/CD and production support. Demonstrates deep microservices experience with RabbitMQ/event-driven architecture, idempotency, DLQs, and compensating logic to maintain reliability and data consistency at scale, plus a track record of replacing spreadsheet-based ops reporting with an adopted real-time internal tool.”

“AI Engineer (Medtronic) who deployed a production RAG-based clinical assistant grounded in curated biomedical literature (no patient-identifiable data). Deep hands-on experience orchestrating and hardening LLM workflows with LangChain/LangGraph, including stateful agentic flows, rigorous testing, and evaluation; reports a 72% accuracy improvement through retrieval enhancements (query rewriting, multi-query expansion, MMR reranking).”

“Built a production agentic AI system to automate data science work using a layered architecture (executive-summary handling, tool-based execution, and on-the-fly code generation). Demonstrates strong end-to-end agent development practices including RAG with vector databases, prompt engineering, and multi-method evaluation (LLM-as-judge/human/code-based), plus Airflow-based orchestration for ML data pipelines and close collaboration with business end users.”

“Backend/platform engineer building HIPAA-compliant, real-time healthcare systems: owned a Python/Flask API layer for an AI-enabled patient engagement and risk scoring service, implemented PHI-safe logging and cross-service auditability, and delivered Kubernetes microservices via ArgoCD GitOps. Also has experience with Kafka streaming pipelines and hybrid cloud-to-on-prem migrations in regulated healthcare/fintech environments.”

“Built and shipped a production LLM-powered RAG assistant for enterprise internal document search (PDFs, knowledge bases, structured data), addressing real-world issues like noisy documents, hallucinations, and latency with grounded prompting, retrieval-confidence fallbacks, and performance optimizations. Also partnered with compliance and business teams at JPMc to deliver a solution aligned with regulatory constraints, supported by monitoring, feedback loops, and systematic evaluation.”

“Sole creator of a full-stack C++ 3D drone simulator/visualizer, including a self-contained flight stack (GNC, sensor simulation, flight manager) plus OpenGL-based graphics/UI. Built SITL-ready interfaces via MAVLink over UDP and ROS 2 Humble, and has embedded Linux CI/CD experience using CMake and Jenkins with automated unit/integration testing.”

“Robotics software engineer/researcher at Stanford PDML Lab building VisualFT, a ROS2-based visual-tactile sensing system for compliant force-control guidance in acupressure/ultrasound-style manipulation. Also interned at Neocis (dental robotics) improving safety-critical collision detection using Bullet Physics with automated validation and CI (Jenkins/CDash).”

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

“Full-stack developer who built a learning management web app end-to-end using React, Spring Boot, and MySQL, integrating APIs via Axios and validating/testing with Postman. Has experience handling data-heavy workloads (courses, quiz results) and improving performance with pagination, and is comfortable designing microservice-style endpoints with CI/CD considerations.”

“Built a production assistive-vision iPhone app to help visually impaired users find grocery items, training a custom YOLO detector on 2,000+ self-collected/annotated images and deploying via CoreML with a cloud multimodal LLM for navigation instructions. Brings hands-on AWS serverless + ECS container deployment (CDK/GitHub Actions) and a disciplined approach to AI workflow reliability (state-machine design, offline evals, stress tests, logging/metrics), plus experience communicating model insights to non-technical stakeholders (MOTER Technologies).”

“AI/ML engineer (Cognizant) who built a production, real-time credit card fraud detection platform combining deep-learning anomaly detection with an LLM-based explanation layer. Strong focus on regulated deployment: addressed class imbalance and feature drift, and added guardrails (SHAP/structured inputs, fine-tuning on analyst reports, rule-based validation) to keep explanations accurate and compliant. Orchestrated the full pipeline with Airflow + Databricks/Spark and used MLflow/Prometheus plus A/B and shadow deployments for measurable reliability.”

“ML/LLM engineer who has shipped a production transformer-based document understanding system on AWS, owning the full pipeline from domain fine-tuning to Dockerized CI/CD deployment. Demonstrates strong production rigor—latency optimization (distillation/quantization, async batching, autoscaling), orchestration with Airflow/Step Functions/Azure Data Factory, and monitoring/drift detection—plus experience translating ops stakeholder needs into adopted AI automation via dashboards.”

“Data/ML engineer with experience across pharma (Dr. Reddy Laboratories) and financial services (Cincinnati Financial, Capital One), building production NLP and entity-resolution systems that connect messy unstructured text with enterprise SQL data. Delivered semantic search with BERT + vector DB and domain fine-tuning (reported ~35% relevance lift), and builds robust pipelines using Airflow/dbt/Spark with strong validation, monitoring, and stakeholder-aligned rollout practices.”

“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”

“Senior engineering leader with experience at Disney and BlackLine who drives business-aligned technology roadmaps through deep Product/Engineering partnership (two-in-a-box) and pragmatic prioritization frameworks. Has led major modernization initiatives—private-to-public cloud migration to GCP with multi-cloud evolution, data-layer performance improvements (Mongo/Redis, caching/query optimization), and tooling upgrades (VSS to GitHub)—while scaling teams with strong quality and accountability culture.”