Vetted C++ Professionals

“Solutions Architect with hands-on experience driving AWS Partner Network engagements end-to-end (technical reviews, discovery, demos, incentives, marketplace/GTM) to enable revenue outcomes, even when not the direct closer. Known for navigating complex policy/compliance changes with high-revenue partners and for being a go-to Amazon Connect specialist in ambiguous customer environments; also collaborated with founders of a small health tech company on an AI agent concept tied to healthcare workflows and medical records.”

“End-to-end deployment owner for Oracle document delivery/print services in a hospital-like production environment, focused on reliability/performance at scale (thousands of systems). Also describes implementing event-driven RAG/agentic LLM workflows with attention to embeddings/index consistency, latency, and measurable improvements in response relevance and operational efficiency.”

“Built Baioniq, an enterprise LLM platform for automating extraction from massive unstructured documents like contracts and insurance claims. They demonstrate unusually strong production depth in agentic AI—scaling to 100k+ requests/day, processing 1M+ claim documents, and improving extraction accuracy through rigorous RAG architecture, evaluation, and fallback design.”

Sirisha Maddikunta

Screened

Mid-level Generative AI Engineer specializing in enterprise LLM and healthcare AI solutions

O Fallon, MO6y exp

“Built and owned an end-to-end LLM-powered fraud investigation assistant that automated case summaries and risk analysis, cutting analyst investigation/documentation time by 40%. Stands out for translating RAG concepts into a production-grade internal platform with strong evaluation, monitoring, and reusable Python service architecture that improved both analyst trust and engineering velocity.”

Kiran Kumar

Screened

Mid-level Software Engineer specializing in Java microservices and GenAI automation

USA4y exp

“Software engineer (4+ years) with hands-on production GenAI experience: built an AI incident triage assistant that summarizes production logs for on-call engineers and iterated it using real incident metrics (time-to-signal, triage duration). Also shipped a RAG-based customer support knowledge assistant using embeddings + vector retrieval with strong guardrails (relevance thresholds/abstain, sanitization, auditing) and a formal eval loop (500-query gold set) that drove measurable retrieval improvements.”

“Architecture leader from Disney who managed system, AI, and data architects while staying hands-on in solution design. Has experience building LLM-based video advertising products, designing Kafka-based real-time data architectures, and using MVP/POC approaches to align product and executive stakeholders.”

“Frontend/product engineer from IXL who built an AI workspace for teachers to generate, edit, and chain classroom resources using LLMs. They show unusual depth in browser fundamentals and rich-text/math UI work, including debugging a rare repaint issue and designing mixed text/LaTeX editing experiences for educators.”

Ranfei Pang

Screened

Mid-level Software Engineer specializing in AI systems and FinTech

Boston, MA4y exp

“Amazon warehouse-tools engineer with strong full-stack and GenAI systems experience, spanning large-scale provisioning platforms and internal LLM/chatbot products. They’ve owned systems end to end, including React/TypeScript frontends, Java/AWS backend orchestration, and Bedrock-based RAG architectures, with measurable impact on latency, token cost, validation quality, and operational support load.”

“Robotics software engineer with hands-on experience migrating a robotics project from ARM to AMD by building a Dockerized environment with PyTorch/CUDA dependencies, improving data processing and battery efficiency. Has integrated ROS 2 nodes for a Time-of-Flight camera and debugged motion-planning issues (tight-turn stopping) using data collection and iterative tuning; also built custom robots in Webots for sensor/actuator-driven behaviors.”

“Software Design Lead on a NAVAIR-sponsored senior design capstone building an Unreal Engine 5 UAV/LiDAR simulation to support sensor spoofing detection. Reverse-engineered and standardized LiDAR packet formats and integrated the sim with Simulink and an NVIDIA Jetson Orin Nano over Ethernet to enable stable real-time SIL/HIL testing, leveraging strong Linux/kernel networking knowledge to debug latency and packet loss.”

“MSR robotics candidate who led a 4-person project building a ROS2 MoveIt wrapper for a Franka Emika arm and integrating a RealSense-based vision pipeline for color-based object tracking/sorting. Also building a quadruped with ROS on Raspberry Pi, bridging ROS commands through a motor driver to TTL-controlled motors, and expanding from Python ROS development into C++ for navigation/LiDAR/SLAM work on TurtleBot3.”

“Backend engineer with production experience on an AWS Lambda-based payment service (manually deployed) and hands-on modernization work using parallel-run + diffing to prove parity before cutover. Has practical production troubleshooting experience for batch/pipeline incidents using monitoring/logs and emphasizes idempotent rerunnable jobs for safe recovery; also improved GraphQL performance by refactoring overly broad queries.”

“Unity VR/MR developer with multiple shipped Meta Quest projects, including a multi-user mixed-reality co-creation experience featuring real-time connection logic and shader-driven mesh generation for performance. Also builds AI-powered interactive applications, recently creating a video interview simulator using OpenAI API, HeyGen real-time avatars, and AWS audio/agent tooling while managing end-to-end latency challenges.”

“Backend-focused Python engineer who built an end-to-end personalized chatbot service integrating Amazon Redshift context retrieval with Amazon Bedrock, including prompt construction and production-grade reliability controls. Strong platform experience deploying containerized services to Kubernetes with GitOps/ArgoCD, plus hands-on Kafka streaming and phased infrastructure migration execution.”

“AI/ML practitioner who built an Indian Sign Language recognition system (MediaPipe hand keypoints + CNN/RNN) as an accessibility-focused teaching aid, iterating closely with advocacy groups and educators and reaching 92% accuracy. Also has production-scale data migration experience at Saasgenie, using Kubernetes pod parallelization to migrate 1M+ ITSM records with a 5x throughput gain under API rate limits.”

“Full stack engineer in the financial/thematic investing domain who built end-to-end applications on AWS. Notably redesigned a slow portfolio analytics workflow by offloading heavy computations to scheduled AWS Lambda jobs and caching results in DynamoDB (TTL), cutting API latency from ~5 seconds to under 300ms while supporting data-heavy daily market processing.”

“Backend-heavy full-stack engineer with experience at Intuit (TurboTax Live) and Paytm payments, building and scaling Java/Spring Boot microservices for high-traffic transaction systems. Has hands-on wins improving peak-load performance using Redis/disk caching and Kafka event-driven patterns, plus React/Redux work for web app integration and strong monitoring practices with ELK.”

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

“Robotics software engineer who led localization/SLAM work on an autonomous indoor security drone operating in a pre-mapped environment. Implemented a robust localization strategy combining visual PnP loop closures with point-cloud ICP to mitigate issues like visual map aging, and uses ROS tooling (rosbag/TF/RViz) plus Gazebo and Docker for repeatable debugging, simulation, and development.”

“Customer support professional with Scrum Master and Product Owner certifications who has handled high-stakes account security incidents (including locking down an account to protect over $200k) and troubleshot live data feed integrations (XML/socket) by identifying IP whitelisting mismatches. Emphasizes transparent stakeholder communication, escalation, and building internal wiki documentation to prevent repeat issues.”

“Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.”

Lavanya Chilakalapudi

Screened

Mid-level Full-Stack Developer specializing in cloud-native web apps and APIs

Tampa, FL5y exp

“Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.”

Madhu Swetha Kommi

Screened

Intern Full-Stack Software Engineer specializing in cloud data pipelines and internal tools

1y exp

“Built an internal Meta tool (HiVA Bot) for notification customization and end-to-end task tracking around advertiser-reported issues, including chat-thread creation, org-hierarchy opt-ins, SLA reminders, and search/typeahead features. Implemented the system with a Java/Spring Boot microservices approach and asynchronous patterns, and supported adoption via internal wiki documentation.”

Shobana Chandrasekaran

Screened

Mid-Level Software Engineer specializing in AI microservices and generative fashion

Sunnyvale, CA2y exp

“Backend/AI workflow engineer at a startup building production AI services for fashion workflows, including an AI-powered techpack generation API in Go (Gin) with MongoDB handling ~1k+ daily requests. Recently implementing an image-to-3D dress generation feature end-to-end, integrating a Python FastAPI AI service with ComfyUI + Hunyuan, with strong emphasis on async orchestration, webhooks, and observability (OpenTelemetry + SigNoz).”