Vetted C++ Professionals

“New grad candidate with graduate research experience building a multi-agent RAG pipeline from scratch, including worker-coach orchestration and an evaluation framework. Most notably, they improved structural similarity from 67% to 98% by designing validation and retry logic to reduce hallucinations, showing strong practical depth in agentic AI systems.”

“Full-stack and applied AI candidate who has shipped both a shift-management workflow product and an LLM-powered business insights system using Athena, S3, and Bedrock. They show strong grounding in prompt design, retrieval-based AI architecture, and practical human-in-the-loop product judgment, while also working in an early-stage university research project focused on accessibility for hard-of-hearing users.”

“Full-stack engineer who built an early-stage social platform for scriptwriters (Scriptscape) from scratch, owning everything from React Native/React UX to Node/Postgres APIs and AWS deployment. Demonstrates strong production-minded engineering with CI/CD, observability, and scalability patterns (cursor pagination, indexing, background jobs), plus experience hardening flaky third-party integrations with idempotency and backfills.”

“Research assistant who single-handedly built and integrated an indoor autonomous wheelchair system using NVIDIA Jetson Nano, LiDAR, and a stereo camera. Implemented a multi-sensor perception pipeline (OpenCV/PCL) with ROS-based modular nodes, TF frame management, and robust debugging via RViz/rosbag, plus simulation testing in Gazebo and Dockerized environments for portability.”

“AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.”

“ROS2/Python robotics engineer who led a 4-person team building a simulated multi-robot warehouse system (SLAM + NAV2 + centralized task allocation) in Gazebo Ignition, including a distance/priority-based controller that reduced task completion time by ~30%. Also has hands-on real-time debugging/tuning experience for both mobile robots and a MyCobot 600 Pro manipulator, plus simulation work in CARLA using RL (TD3) and Social-LSTM for pedestrian behavior modeling.”

“Backend engineer who has designed and evolved high-traffic event/activity management systems using Node/Express and PostgreSQL, prioritizing scalability and reliability with a layered architecture. Has led zero-downtime refactors/migrations using parallel runs, dual writes, and rigorous validation/monitoring, and brings a security-focused API approach (JWT, RBAC/ABAC, rate limiting, DB-enforced tenant/RLS filters).”

“Backend engineer with deep experience modernizing a provider credentialing/compliance platform with multiple upstream/downstream integrations. Focused on building predictable, scalable REST APIs (primarily ASP.NET Core; framework-agnostic approach applicable to FastAPI), improving performance via DB/query optimization, and hardening workflows with idempotency, transactions, feature flags, and strong auth/RBAC patterns.”

“Built and deployed an agentic RAG platform at Centene Health to support healthcare claims and complaints workflows (Q&A for claims agents, executive complaint summarization, and compliance triage/classification). Experienced in LangChain/LangGraph orchestration, production deployment on AWS with FastAPI/Docker/Kubernetes, and implementing HIPAA-compliant guardrails to reduce hallucinations and ensure explainable outputs.”

“Developed and deployed CaptionFace, a production vision-language system that boosts low-resolution/surveillance face recognition by generating discriminative natural-language captions (ViT encoder + GPT-2 decoder) and enabling text-to-face retrieval and zero-shot recognition. Orchestrated distributed training on Kubernetes with MLflow tracking, mixed-precision optimization, and comprehensive evaluation including out-of-domain robustness; collaborated with non-technical NSF project stakeholders via demos, visualization, and clear documentation.”

“Early-career CS/data professional with hands-on experience integrating analytics dashboards into a production MERN system, including a Redux state redesign and schema validation that delivered zero-downtime release and measurable performance gains (~30% faster APIs, 25% faster reporting). Previously a data analyst at Reliance Jio, where they extended Python-based reporting pipelines (CSV/MySQL) with automated validation and anomaly detection to improve KPI dashboard reliability and cut investigation time by ~30%.”

“Backend-focused engineer who owned an AI mentoring workflow platform built in Django with LangGraph multi-agent orchestration, optimizing it to stay under 200ms latency while scaling past 1,200 active users using profiling, caching, load testing, and OpenTelemetry-style tracing. Also has hands-on experience containerizing and deploying Python/ML services to AWS ECS via GitHub Actions/GitOps, and building reliable real-time pipelines with webhooks and Redis queues (idempotency, backpressure, DLQ).”

“Robotics software engineer who built a ROS/C++ workcell stack to automate coating wooden panels with a 6-DOF arm, including trajectory generation, MoveIt/OMPL planning, and a single launch/config setup that runs in both Gazebo and on real hardware. Strong in debugging real-world planning failures (e.g., intermittent aborted/no-plan regions) through logging, planner swaps, and collision/kinematics tuning, and in designing modular ROS/ROS2 systems with versioned interfaces and translation layers for heterogeneous robots.”

“Deployment engineer at a robotics startup who owned end-to-end field deployments in greenhouse environments, including integrating humanoid robots (XArm 6), tuning perception stacks for real-world lighting shifts, and coordinating rapid fixes with hardware/software teams. Experienced debugging complex robotics integrations (LiDAR + NVIDIA Jetson + ROS2 + networking) and hardening solutions by automating configuration at boot, while also working directly with customers and training operators for ongoing support.”

“LLM/RAG-focused engineer who repeatedly takes agentic workflows from impressive demos to dependable production using rigorous evals, SLOs, and deep observability. Has led high-impact incident mitigation (22-minute MTTR during a major sale) and developer enablement workshops, and partnered with sales to close a $410k ARR enterprise deal with a tailored RAG pilot (FastAPI/pgvector/Okta/InfoSec-ready).”

“Backend engineer who built an Emergency Alert System with Virginia Tech for the City of Alexandria, focusing on real-time ingestion, secure dashboards, and AI-assisted prioritization. Emphasizes high-stakes reliability with guardrails (hybrid rules+LLM, confidence-based fallbacks), scalable async processing, and defense-in-depth security (JWT/RBAC plus database row-level security).”

“Founding engineer with strong end-to-end product delivery across IoT + mobile + serverless cloud: built firmware for a Bluetooth-connected device (ESP32), a native Swift iOS app, and an AWS serverless backend (API Gateway/Lambda/SQS/SNS/DynamoDB) including payments via Stripe. Also shipped a separate startup product in 6 months: a React visual tool that generated HTTP/REST APIs with a Django backend, admin panel, and a code-generating CLI.”

“Gameplay/systems developer with shipped VR experience on Meta Quest (Litesport), owning a real-time workout scoring and progression system end-to-end including hit validation, HUD/UI, session state, and persistence. Known for event-driven architecture that decouples gameplay from UI, data-driven tunables for multiple modes, and rigorous VR performance work to hold 72 FPS using on-device profiling and debugging.”

“Game developer/designer with professional Unity experience and personal UE5/Godot projects, focused on improving player comprehension through subtle UX/environmental guidance. Has built end-to-end gameplay systems (FPS hitscan, health, saving/serialization, basic AI with A* and state machines) and shipped mobile titles on Google Play, including a physics-based trajectory/prediction feature that received positive feedback.”

“Backend/AI engineer who has shipped production LLM systems end-to-end, including an AI request-routing service (FastAPI + BART MNLI + OpenAI/Gemini) that improved accuracy ~25% after launch via eval-driven prompt/category iteration. Also built an enterprise document intelligence/RAG platform on Azure (Blob/SharePoint/Teams ingestion, OCR/NLP chunking, embeddings in Azure Cognitive Search) with PII guardrails (Presidio), confidence gating, and scalable event-driven pipelines handling millions of documents.”

“AI research engineer who has built and tested LLM agents end-to-end, including a Telegram real-time voice-to-typing assistant integrated with calendar scheduling. Emphasizes production concerns (security via mic-triggered activation, multi-model fallbacks, monitoring) and agent predictability using a GPT-3.5-based critic plus structured outputs (Pydantic) and ReAct-style orchestration.”

“Engineering leader/player-coach who redesigned A/B testing and observability infrastructure for real-time audio/video features at 90M+ DAU scale, using Kafka-based ingestion and horizontally scalable aggregation for near real-time metrics. Managed 10–15 engineers, drove >20% infrastructure cost reduction without user-experience regressions, and led major peak-traffic incident response with lasting reliability improvements (load testing, capacity planning, alerting, pre-mortems).”

Likhith Kumar Yaramala

Screened

Junior Backend/Cloud Software Engineer specializing in microservices and DevOps

India2y exp

“Cloud/DevOps-focused engineer with strong Linux production operations experience, deploying microservices to AWS on Docker/Kubernetes. Has built and operated secure CI/CD (GitHub Actions/Jenkins) and Terraform IaC workflows with approvals, remote state, and drift detection, and has hands-on incident recovery experience in containerized environments; limited direct IBM Power/AIX/PowerHA exposure.”