Vetted C++ Professionals

“Robotics software engineer who built and owned an autonomous laparoscope tracking system on a UR3e with an eye-in-hand RealSense camera, integrating YOLO-based tool detection with velocity control under a strict RCM constraint and deploying successfully in a hospital setting. Deep ROS2/MoveIt2 experience (architecture, QoS, custom nodes) plus autonomy stack work across SLAM, planning, and real-time latency/control debugging.”

“LLM engineer who has deployed privacy-preserving, real-time workplace risk monitoring over massive enterprise chat/email streams, tackling latency, hallucinations, and extreme class imbalance with model benchmarking, RAG + fine-tuning, and a pre-filter alerting layer. Also built an agentic legal contract drafting system (Jurisagent) using LangGraph/LangChain with deterministic multi-agent control flow, structured outputs, and reliability-focused evaluation/telemetry.”

“Built a production LLM-powered analyst assistant at Discern Security to speed up SOC investigations using a RAG pipeline over security vendor documentation (Python PDF ingestion, vector search). Demonstrates deep, security-critical LLM engineering: structure-aware chunking with custom table parsing, grounded/cited responses, prompt-injection defenses, and post-generation validation, validated via golden datasets and adversarial testing; tool is used daily by analysts.”

“Software engineer who owned customer-facing, high-traffic TypeScript/React + TypeScript backend systems end-to-end, emphasizing safe velocity through feature flags, staged rollouts, observability, and rollback-ready incremental delivery. Reports shipping more frequently with fewer production incidents and faster recovery due to these guardrails.”

“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”

“Built and shipped a production LLM-powered investor research feature for a fintech product, focused on grounded answers and minimizing hallucinations. Implemented retrieval-quality and evidence-coverage gating with clear refusal fallbacks, and evaluates systems with regression tests and metrics like correct-refusal rate, hallucination rate, and latency. Comfortable orchestrating workflows with LangChain or custom Python depending on production needs.”

“Built a hackathon "Patient Summary Assistant" backend focused on healthcare workflows, combining RAG-based summarization with HIPAA-minded privacy controls (NER redaction + encryption). Demonstrated strong infra skills by deploying on Kubernetes with Helm/HPA and GitOps (ArgoCD), plus migrating from OpenAI to an on-prem Llama 3 stack (vLLM, quantization, shadow-mode testing) and adding real-time Kafka ingestion for patient vitals/anomaly alerts.”

“Built and productionized a RAG-based analytics Q&A assistant for a financial analytics team, enabling natural-language querying across 200+ datasets (SQL tables, PDFs, compliance docs, wikis) and cutting turnaround time by 60%. Deep experience delivering regulated, audit-ready LLM systems on Azure (Azure OpenAI + LangChain) with strict grounding/citations, hybrid retrieval, and AKS-based low-latency deployment, plus strong collaboration with compliance analysts and auditors via iterative Gradio demos.”

“Built and deployed a production RAG-based multi-agent chatbot during an internship to help consultants answer client questions and guide users through new IT systems with step-by-step instructions. Demonstrates hands-on experience with LangGraph/LangChain/Google ADK, unstructured document parsing and chunking for RAG, and a reliability-first approach to agent workflows (metrics, fallbacks, human-in-the-loop, guardrails).”

“ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).”

“Backend/ML-systems engineer with experience (including Amazon) building real-time face recognition services using PyTorch (MTCNN/FaceNet) and AWS (SQS/S3/Lambda/EC2) with a focus on low latency, burst handling, and cost control. Also led a revenue-critical legacy pricing workflow migration to a serverless event-driven architecture using strangler-pattern rollout, simulation-based validation, and strong security practices (JWT/RBAC/RLS).”

“At Citi, helped lead the productionization of an internal LLM-driven automation workflow into a production-ready developer platform, focusing on determinism/reproducibility, security, and cost controls. Implemented prompt versioning/registry, JSON schema validation, sanitization, and deep telemetry (including manual edit-distance) plus human-in-the-loop review and phased rollout—driving major SDLC efficiency gains (e.g., test script creation cut from ~1 week to ~1 day).”

“World of Warcraft quest designer who owned end-to-end quest pipelines and shipped standout content, including the memorable escort/stealth quest “Klaskin’s Great Escape” tuned through playtests and a Dragonflight capstone framing story that drove higher side-quest engagement. Experienced in Lua scripting, reward/economy balancing, and building daily/weekly endgame loops (Beetle Ranch/Rak-Ush), with recent UE5 Avalanche node-based VFX prototyping exposure.”

“Player-coach engineering leader focused on consumer-grade video/multimodal products and high-reliability identity/auth experiences. Led design and implementation of multi-step mobile login/MFA flows with telemetry-driven funnel improvements, shipped Node services and security fixes, and owned auth incidents end-to-end using RUM and step-level instrumentation. Introduced feature-flagged delivery and targeted review/testing practices to speed iteration ~20–30% while keeping login stability high.”

“Full-stack engineer and KICKOFFUSA cofounder who built production payment/registration and live tournament experiences under real matchday load (200+ concurrent users), including Stripe webhooks with idempotency and UX improvements that cut checkout abandonment ~15%. Also owned an end-to-end research hub at a GTSCL internship—designed a normalized Postgres schema and full-text search (tsvector/GIN) delivering sub-100ms queries for 300+ researchers.”

Shanmukha Koganti

Screened

Mid-level AI/ML Engineer specializing in recommender systems and edge computer vision

Bay Area, CA6y exp

“ML/AI engineer with production experience at Shopify and Intel, building a deep learning product ranking system that lifted add-to-cart ~14% and serving real-time similarity search via FAISS+Redis under <20ms latency at massive scale. Also deployed computer vision models to 100+ retail edge locations using Docker/Ansible/k3s with zero-downtime rollouts, and applies strong MLOps practices (A/B testing, canary/shadow, observability) plus performance optimization (OpenVINO, INT8).”

Pratima Singh

Screened

Senior Full-Stack Software Engineer specializing in FinTech, cloud microservices, and blockchain

Tempe, AZ10y exp

“Python/ML engineer with strong DevOps depth: built an end-to-end regime-aware stock prediction system (custom fine-tuned FinBERT sentiment + technical/macro features) delivering a 12% accuracy lift. Also implemented Kubernetes/Helm + Jenkins/GitHub Actions pipelines (including GitOps-style workflows for multi-cloud Hyperledger Besu) and improved deployment speed/stability by ~50% while addressing race conditions and image drift.”

Nagarjuna Vaddineni

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines

Seattle, WA6y exp

“Amazon backend engineer who built and operated high-scale Java Spring Boot microservices on AWS (EKS/EC2) handling millions of daily transactions, with deep experience debugging p95 latency and database/ORM bottlenecks. Shipped an AI-driven real-time personalization feature by integrating SageMaker model inference end-to-end with low-latency caching and graceful fallbacks, and designed robust order/payment orchestration with retries, compensations, and DLQ-based escalation.”

Amit Sharma

Screened

Principal Software Engineer specializing in AI/LLM platforms, payments, and healthcare systems

San Francisco, CA25y exp

“Engineering player-coach who recently shipped an agent-based workflow to extract key info from unstructured web data (browser agents + CDP) and populate daily digests/calendars, owning architecture through testing. Also built a Flask-based LLM evaluation and regression testing system using G-Eval/Confident AI dashboards, and applies a rigorous, research-driven approach to selecting third-party tools with stakeholder buy-in; has healthcare ops/onboarding workflow experience at Vivio Health.”

Erik Wilkinson

Screened

Senior Game Designer specializing in systems, combat, and live-ops game modes

Allen, TX19y exp

“Game designer with shipped experience on Squid Game Unleashed (mobile) and Radical Heights (battle royale), owning multiple modes end-to-end from paper design and greybox through tuning, QA, and live ops/backend rollout. Demonstrates strong Unreal/Blueprint prototyping, pacing-focused iteration (targeting 70–90s rounds), and building meta challenge systems that stay fresh via monthly/seasonal rotations and player-feedback-driven map weighting.”

Atulya Bist

Screened

Junior Data Scientist / Software Engineer specializing in LLM analytics and robotics

Los Angeles, CA3y exp

“Robotics/ML engineer who implemented TD3 and PPO in PyTorch to solve the challenging OpenAI Gymnasium humanoid-v5 MuJoCo task, including custom networks, rollout logic, and training scripts. Also has hands-on robotics coursework experience with ROS-based RRT motion planning on a real robotic arm, plus practical CI/CD and containerization experience (Docker, Jenkins, GitHub Actions). Currently exploring world models (VAE + sequence generator) using Euro Truck Simulator data.”

Sahil Kakadiya

Screened

Junior Embedded Systems & Wireless Software Engineer specializing in BLE/Wi-Fi performance

Mountain View, CA2y exp

“Master’s capstone contributor on an autonomous rover navigation project, serving as an embedded/robotics software designer. Built low-level wheel control and odometry from encoders, integrated RealSense and RPLidar via ROS, and solved sensor-fusion/coordinate-frame issues by creating custom TF transforms. Used Gazebo to debug sim-to-real behavior and improved reliability on rough terrain by moving to dual-channel encoders when IMU data proved unreliable.”

“Built production-grade Python systems in a medical/imaging context, including an image feature extraction and survival prediction microservice with strong testing, validation, and observability practices. Also developed a Playwright-based autonomous job application agent that handled dynamic UIs and anti-bot challenges with stealth tooling, proxies, and human-in-the-loop escalation.”