Vetted CSS Professionals

Aaditya Voruganti

Screened ReferencesStrong rec.

Junior AI & Software Engineer specializing in robotics and ML infrastructure

2y exp

“Robotics engineer from UIUC’s Intelligent Motion Lab who led the perception stack for a humanoid robotic nurse, fusing camera/LiDAR/IMU on NVIDIA Jetson Orin for real-time localization and scene understanding across six robots. Deep expertise in ROS 2 and edge ML optimization (TensorRT, CUDA, zero-copy), delivering major latency/throughput gains (10 FPS to 22+ FPS) and building fault-tolerant pipelines with gRPC offloading and real-time reliability practices.”

MichaelJose Oakes

Screened ReferencesStrong rec.

Senior Unity/XR Engineering Manager specializing in real-time interactive and multiplayer experiences

9y exp

“Unity Technologies engineer with direct Meta subcontract experience shipping Quest titles (Horizon Worlds projects like Super Rumble) and supporting third-party studios. Strong in VR performance optimization and modernization work—porting legacy OVR/older-Unity projects to OpenXR, URP, and hand-tracking inputs. Built a master’s dissertation cross-platform multiplayer FPS spanning Quest VR, PC, and mobile AR using Photon.”

“Backend engineer who evolved the X-Ray gaming analytics platform, leading a zero-downtime MongoDB→AWS DocumentDB migration with dual-write, checksum-based validation, and Kubernetes canary rollouts while maintaining real-time monitoring for millions of concurrent sessions. Strong in FastAPI/Python API scaling and performance tuning (cut latency from ~2s to <150ms and reduced DB load 90%) plus production-grade auth/RLS security patterns (JWT, Supabase Auth, PostgreSQL RLS).”

“Product/UX designer with end-to-end ownership of Dell’s “Parts for Your Dell” multi-device shopping experience, using 30+ usability tests and A/B testing to drive a 28% conversion lift and 40% satisfaction increase. Experienced translating complex hardware compatibility logic into guided flows, building cross-viewport design systems, and collaborating closely with engineers on edge cases and component implementation; also prototyped gamified micro-interactions at upGrad and completed a GenZ-focused fintech capstone with PNC.”

“Backend engineer with hands-on experience building Python/Flask microservices using PostgreSQL/SQLAlchemy, JWT auth, Docker, and GitHub Actions CI/CD. Strong in performance and scalability work—migrated heavy processing to Celery/Redis, tuned queries with EXPLAIN ANALYZE and indexing, and delivered 50%+ API latency reduction. Also integrates AI workflows (OpenAI APIs) with batching/caching/fallbacks and has implemented multi-tenant data isolation patterns.”

“Interned at SLB and owned an end-to-end GenAI chatbot deployment for a finance team, including invoice PDF data extraction and an LLM-driven layer (LangGraph/LangChain) that translated natural language to SQL and returned results in natural language. Validated LLM JSON outputs against benchmarks using DeepDiff and deployed the solution via Docker to Kubernetes, managing pods with k9s.”

Surya Teja

Screened

Mid-level Backend/Full-Stack Engineer specializing in AI and FinTech payments

Tempe, AZ4y exp

“Full-stack engineer who has owned an operational reporting/dashboard product end-to-end—building a React UI, designing/implementing FastAPI services, and deploying/operating on AWS. Demonstrates strong performance engineering (Postgres query/index tuning using EXPLAIN ANALYZE) with concrete impact (reports reduced from tens of seconds to a few seconds) and a reliability mindset across observability, migrations, and resilient third-party/ETL integrations.”

“Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.”

“Frontend tech lead at HubSpot who shipped an LLM-powered insights dashboard that analyzed complex customer interaction histories and surfaced sentiment, challenges, and next-best actions for sales users. Stands out for having taken an AI feature beyond prototype into beta and full production, with strong emphasis on testing, maintainability, and practical production tradeoffs.”

“Full-stack engineer with a strong mix of real-time product engineering and applied AI experience. Built and deployed a production stock trading simulator on AWS and an LLM-based customer support agent with RAG/tooling, and also shipped a zero-to-one in-store detection feature at Meituan that improved CTR by 7% and conversion by 11%.”

“Backend-leaning full-stack engineer with experience at Liberty Mutual and Airbnb, building high-scale insurance claims systems (1M+ monthly transactions) and consumer booking/pricing services (120K–180K daily requests). Strong in transactional data integrity, PostgreSQL performance tuning, and production operations (Docker/Jenkins/AWS), with measurable UX/performance wins including ~2.3s page loads and significant runtime failure reduction.”

“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”

“Marketing designer/creative lead who builds scalable Figma-based systems for high-volume growth and community creative. Led a Recurly campaign aligned to a brand refresh (including creative testing like light vs dark), and served as the sole designer for Grow Therapy’s inaugural “Grow Forward” summit producing a full suite of event assets plus modular community templates for ongoing programming.”

“Backend/distributed-systems engineer with Uber experience building real-time telemetry and safety signal pipelines. Strong in Kafka-based event-driven architectures, low-latency processing under peak load, and production reliability via monitoring, retries, and fallback logic; has Docker/Kubernetes and CI/CD deployment experience.”

“Early-career engineer (internship background) who built a production-style notes product using Next.js App Router with Server Components/Server Actions and a Postgres-backed analytics model. Demonstrates strong performance and reliability instincts—measured DB latency improvements via indexing and cursor pagination, plus durable orchestration with Temporal using idempotency and deterministic workflows.”

Yeshwanth Sai Pala

Screened

Mid-level Full-Stack Developer specializing in cloud microservices and AI-driven FinTech

Remote, USA4y exp

“Stripe engineer who shipped an end-to-end merchant fraud insights dashboard, spanning Spring Boot/Kafka risk-scoring services and a React+TypeScript UI. Focused on low-latency, high-volume transaction processing and production operations on AWS (EKS/CloudWatch), including handling a real traffic-spike latency incident via query optimization, indexing, and rate limiting.”

Shloka Reddy

Screened

Mid-level Software Engineer specializing in FinTech full-stack development

San Francisco Bay Area, CA3y exp

“Frontend-leaning full-stack engineer with experience spanning early-stage startup work at Rundoo and a higher-trust fintech environment at Wealthfront. They’ve owned complex permission-based household/account experiences end-to-end in Next.js/React, with strong instincts around data flow, UI correctness, performance, and production pragmatism.”

“Built and shipped a production agentic RAG system for healthcare analysts that automated compliance/operations knowledge retrieval across PDFs, reports, and databases. Emphasizes production reliability (monitoring, retries, fallbacks, async queues), strong evaluation/iteration loops, and measurable impact (3–10s responses and ~98% top-k retrieval accuracy).”

“ML/AI engineer with experience at Uber and Scale AI, focused on customer service automation across both classical NLP and generative AI systems. Has owned systems from experimentation through production on AWS, including LLM fine-tuning, RAG optimization, safety evaluation, and internal Python platform tooling that improved consistency and engineering velocity.”

“Built a production AI-powered workflow automation system at Netflix that integrated OpenAI and LangChain with FastAPI services on AWS, cutting roughly 320 hours of manual operational effort. Brings a mix of full-stack product development and practical AI systems experience, with strong attention to reliability, maintainability, and non-technical user adoption.”

KARTHIKBABU VADLOORI

Screened

Mid-level Full-Stack Developer specializing in Spring Boot, React, and cloud microservices

San Francisco, CA5y exp

“Backend engineer with experience at Meta and Accenture building regulated-data systems (healthcare/financial) using Python/Flask and Postgres. Has scaled high-throughput services to millions of daily requests, delivering measurable latency wins (~40% API latency reduction; ~35% faster DB-backed endpoints), and has productionized ML inference services using Docker/Kubernetes and AWS (ECS/SageMaker).”

Zheng Wu

Screened

Junior Software Engineer specializing in backend systems and cloud messaging

Mountain View, CA1y exp

“Data/ML engineer who has owned end-to-end systems across email deliverability/segmentation and production LLM apps. Built a Spark+Airflow segmentation engine that materially improved deliverability (99.9%) and open rates (>50%), and shipped a PDF-to-quiz RAG product using LangChain/Vertex AI/Chroma with strong guardrails and an eval loop that cut hallucinations to <5%.”