Vetted C++ Professionals

Nishant Pathak

Screened

Executive Engineering Leader specializing in cloud-native platforms and security

14y exp

“Former CTO of EzCred, a fintech embedded finance/digital lending infrastructure startup that built an API-first underwriting and servicing platform using alternative data (e.g., GST and bank statements) to cut loan decisions from days to minutes. Helped raise $1M in seed funding, built the engineering org and compliance-ready cloud architecture, and ran partner pilots before the company shut down during COVID-driven lending market contraction.”

“Meta engineer who improved a critical revenue estimation dataset pipeline that was arriving ~6 days late—diagnosed via raw logs/lineage, redesigned legacy scans to only process the needed window, and shipped validation plus freshness/lag dashboards. Delivered ~50% latency reduction (to ~3 days) and regained adoption by running old/new pipelines in parallel with gated cutover and evidence-based customer communication. Applies incident-response rigor to real-time LLM/agentic workflow debugging and regularly runs developer demos/workshops.”

“LLM/Conversational AI engineer who built a production multi-turn dialogue system using LoRA fine-tuning on LLaMA, cutting training compute/memory by 90%+ while maintaining low-latency inference via quantization and streaming generation. Experienced in orchestrating end-to-end ML workflows with Prefect/Airflow/Kubeflow (including hyperparameter sweeps and W&B tracking) and improving agent reliability through benchmark-driven testing, shadow-mode rollouts, and stakeholder-informed guardrails.”

“Internship at BlueFoxLabs building and deploying an AI/ML RAG system for a biopharma client on top of LibreChat, including an AWS Textract ingestion pipeline and PGVector retrieval deployed to AWS EKS. Demonstrated production-minded scalability work by moving from a vertically scaled EC2 setup to a horizontally scaling Kubernetes/EKS deployment, using CI/CD to safely incorporate requirement changes like tabular document data.”

“Backend engineer who scaled a food delivery platform by migrating from a single-service architecture to Spring Cloud microservices with an API gateway and Kafka-based event-driven order pipeline. Reported outcomes include ~50% latency reduction, stable ~2K RPS throughput, and 99.8% uptime, with strong emphasis on safe migrations (dual writes, canaries, schema versioning) and security (JWT/RBAC/Postgres RLS).”

Ravikanth Kasamsetty

Screened

Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms

23y exp

“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”

Sara Rubacha

Screened

Engineering Manager specializing in databases and distributed systems

Weston, FL21y exp

“Aspiring founder exploring an AI automation startup focused on automating processes involved in building companies. Not yet developed specific use cases or raised capital, but describes a clear plan to validate ideas through use-case research, building a pilot, and testing with early customers; not familiar with the VC/accelerator landscape yet.”

George Liu

Screened

Intern Software Engineer specializing in full-stack, backend, and AI agent systems

Fremont, CA1y exp

“Backend engineer with Tesla experience who redesigned vehicle registration into a step-based, region-configured workflow across 4–5 microservices, enabling partial saves and reducing customer drop-off. Has hands-on experience scaling and securing Python/FastAPI APIs (OAuth2/JWT, CORS), migrating cold data from MySQL to MongoDB via Kubernetes CronJobs, and implementing RBAC/RLS with Supabase + Postgres.”

“Backend/data engineer with Amazon supply-chain experience building production serverless Python services and ETL pipelines on AWS (Lambda, API Gateway, S3, RDS, Glue). Has modernized legacy SAS jobs into Python with rigorous parity testing and phased migrations, and has delivered major SQL performance gains (minutes down to seconds) through indexing and partitioning.”

“Robotics engineer/researcher from Stanford’s Assistive Robotics and Manipulation Lab who built a custom tactile-sensing gripper system and ROS 2 data pipeline to classify the number of thin material layers grasped using a transformer-based model. Has internship experience at Motiv Space Systems building ROS 2 hardware abstractions for BLDC motor dynamics simulation, plus hands-on SLAM and manipulation work in Gazebo/MoveIt-based projects.”

“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”

“Backend/platform engineer with experience at Microsoft, Uber, and Gusto building production AI-agent automation systems in Python (AutoGen) and cloud-native microservices on Kubernetes across AWS/Azure. Has delivered zero-downtime migrations and high-throughput real-time streaming pipelines (Kafka/WebSockets/Redis), and is strong in GitOps/ArgoCD-driven CI/CD with reliable rollouts and rapid rollback.”

“Robotics software candidate with hands-on experience building controllers for an Autonomous Underwater Vehicle, including dual-PID control in Python with state-space modeling and a planned path to LQR. Developed ROS nodes for odometry-based localization, waypoint planning, and control command publishing, validated through a custom Gazebo/ROS simulation workflow with control-metric-driven testing. Also worked on F1Tenth simulation and scan-matching localization (PL-ICP), with additional cloud deployment experience using Docker/Kubernetes and CI/CD.”

Sergey Pustovit

Screened

Director-level Data Platform & Analytics Engineering Leader specializing in distributed systems

Irvine, CA31y exp

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

“Gameplay engineer with shipped mobile multiplayer experience on Squid Game: Unleashed, where they owned the Usable Items system end-to-end in Unity/C#. Built a modular ScriptableObject/action-based architecture that let designers create new item behaviors quickly without engineering support, while also handling network sync, prediction-related debugging, and internal validation tooling as the content library scaled.”

“Robotics/embedded engineer with hands-on experience building real-time control systems on RP2040 (hydroponics automation, 1-DOF helicopter stabilization) and full ROS 2 navigation stacks in simulation (URDF, TF, PID, A* in RViz/Gazebo). Demonstrates strong low-level protocol work (timing-sensitive one-wire in C) and rigorous debugging across hardware and software using UART instrumentation and oscilloscope verification, plus reproducible workflows with Docker and CI/CD (GitHub Actions/GitLab, incl. Sandia National Labs).”

“JavaScript/TypeScript engineer from Ridgeline who built a retry feature for failed staging-to-production promotions with pre-promotion health checks. Brings a backend-scaling mindset to runtime performance work (metrics-first bottlenecking, Big-O analysis, async/parallelism, caching) and leverages Cursor/AI tooling to ramp quickly on large codebases.”

“Robotics engineer who helped bootstrap Meta’s humanoid robotics effort, building simulation training and deployment infrastructure for vision-language-action (VLA) models. Evaluated multiple physics backends (Bullet, MuJoCo, Isaac, internal) to minimize sim-to-real gap and addressed control-loop frequency mismatches via sequence optimization/MPC-like approaches and trajectory-output modifications. Published research that contributed a new addition to ROS 2 and has built ROS2 node stacks spanning control, perception, teleop, tactile sensing, and imaging.”

David Gross

Screened

Entry AI Software Engineer specializing in LLM workflows and ML pipelines

Redmond, WA2y exp

“Built an autonomous-agent document indexing concept in a hackathon with Microsoft and The Seattle Times, architecting an Azure-based system (Azure AI Foundry, Cosmos DB, Azure indexing, Copilot Studio) and coordinating closely with the customer team. Also created and pitched a sports matchmaking app (Ludicon), combining user studies, feature implementation, and technical support on sales/investor calls.”

Aditya Sawant

Screened

Mid-level Software Development Engineer specializing in robotics and cloud-based device management

North Reading, Massachusetts3y exp

“Amazon Robotics engineer who deployed and scaled the Lumos camera-based package scanning work cell across EU sort centers (100+ work cells in 5+ sites), enabling remote launches via detailed runbooks and troubleshooting. Strong in AWS IoT/edge systems, with hands-on incident recovery (restored 34 down work cells) and secure multi-compute certificate provisioning using IoT Jobs, ACM/CA, and custom roles; delivered ~75% per-cell cost reduction vs Cognex-based approach.”

Pratham Thukral

Screened

Mid-level Software Engineer specializing in distributed systems on AWS

Seattle, WA3y exp

“Data/infra engineer with AWS DynamoDB experience who has shipped reliability-critical systems (Global Tables replica repair protocol) and customer-facing service rollouts using canary/percentage-based deployments, strong observability, and rollback strategies. Also built end-to-end Airflow pipelines producing weekly automated reports over ~10TB of advertising segment data, with rigorous week-over-week data quality validation.”