Vetted Unit Testing Professionals

“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.”

“Candidate has developed a disciplined AI-first engineering workflow that combines design docs, prior PR analysis, testing plans, and multi-agent coordination to accelerate delivery without sacrificing quality. They described acting as a tech lead for AI agents, overseeing code structure, business logic, testing, and service contracts, and reported reducing manual coding effort by nearly 80%.”

“Full-stack engineer with AWS Skill Builder experience building internal content-management and search workflows in TypeScript across React and Node.js. They drove a shift from keyword to semantic search using OpenSearch and Bedrock Titan Embeddings, delivering a 5x reduction in discovery time while also improving production reliability and observability for large-scale content workflows.”

“Full-stack/backend-leaning engineer who has built internal operational dashboards and AI assistants, including a real-time dashboard used by engineering, operations, and management teams at NVIDIA. Brings a mix of Spring Boot, Angular/TypeScript, distributed-system performance tuning, and practical LLM integration with grounding, validation, and production monitoring.”

Jenya Rusinova

Screened

Mid-level Frontend Engineer specializing in cloud enterprise applications

East Palo Alto, CA3y exp

“Frontend-focused product engineer with experience owning production launches in observability/monitoring, including extending an existing web-only service to support mobile users without disrupting current customers. Stands out for balancing speed and safety through feature flags, regional beta rollouts, bug bashes, and close collaboration with PM, design, and backend teams in ambiguous environments.”

“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.”

“Full-stack engineer with deep serverless AWS experience who built VidToNote, an AI video analysis platform, end-to-end using Next.js App Router/TypeScript and an event-driven pipeline (API Gateway, Lambda, DynamoDB, S3, Step Functions, SQS). Strong on production reliability and observability (CloudWatch, X-Ray, structured logging), plus data/analytics work in Postgres with measurable query optimizations and durable LLM evaluation workflows. Amazon background; integrated 22 AWS services and completed AWS Solutions Architect Professional certification within a month.”

“Full-stack engineer in the investment tracking/financial reporting space who built an automated reporting dashboard and compliance/reporting pipeline end-to-end using Next.js (App Router, server/client components), REST, and Postgres. Demonstrated measurable performance wins (~30% faster loads) through caching and query optimization, and built durable orchestrated workflows in n8n with retries, idempotency, and reconciliation checks.”

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.”

“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.”

“LLM/RAG engineer who built a production-style multi-agent orchestrator for resume-to-recommendation workflows (PDF ingestion through screening and recommendations), emphasizing prompt tuning and strict JSON output contracts. Currently building a RAG application for an NGO using Airflow (DAGs + embeddings) and tackling messy, missing/imbalanced data; has hands-on retrieval stack experience (FAISS/HNSW, bge embeddings) and uses rigorous evaluation metrics for groundedness and hallucination control.”

“Backend owner at Apple for an AI workflow orchestration service, with hands-on experience stabilizing peak-traffic production systems using OpenTelemetry-style tracing, bounded async concurrency, and database performance tuning. Built and shipped a Python LLM-agent orchestration layer to automate multi-step operational workflows, emphasizing guardrails, auditability, and deterministic fallbacks to keep non-deterministic AI behavior production-safe.”

“Gameplay engineer with hands-on ownership of a real-time C++ combat ability system, including diagnosing and eliminating large-scale combat frame spikes by refactoring hit detection to an event-driven, animation-notify approach (cut collision checks ~80%). Also implemented UE5 networked abilities (dash) with client-side prediction and server-authoritative reconciliation, plus projectile ballistics validated through debug spline visualizations and unit tests.”

Shreya Roy Koneri

Screened

Mid-level Software Engineer specializing in backend microservices and real-time payments

Phoenix, AZ5y exp

“Product-minded full-stack engineer who has owned customer-facing platforms end-to-end, including a unified web UI platform that increased adoption by 30% using feature flags and phased rollouts. Experienced designing TypeScript/React systems with microservices and RabbitMQ at scale, addressing reliability issues with DLQs, retries, and idempotent consumers, and building internal analytics tooling adopted company-wide within weeks.”

Siddhik Reddy Kurapati

Screened

Junior Controls & Motion Planning Engineer specializing in MPC, RL, and autonomous systems

Boston, Massachusetts2y exp

“Robotics researcher focused on learning-based navigation: builds sub-goal generation and cost-to-go models (Bayesian network-based) integrated with motion planning and MPC/NMPC control. Has hands-on ROS 2 package development across vehicles, drones, and manipulators, and uses a broad simulation stack (Isaac Sim, Gazebo, MuJoCo, PyBullet, PX4) to test and integrate systems.”

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).”

Jingyao Chen

Screened

Junior Backend/Platform Engineer specializing in AI microservices and cloud-native systems

Pittsburgh, PA2y exp

“Cofounder at MeowyAI who shipped a production multimodal (vision/voice/text) AI task manager using Gemini, tackling real-world issues like hallucinations, tool-calling safety, and RAG-based preference memory. Also built a production multi-agent RAG system orchestrated with LangGraph (and contributes to LangChain), with strong emphasis on latency optimization, observability (OpenTelemetry), and rigorous testing/evaluation including A/B tests and adversarial prompting.”

Sri Charan Reddy Mallu

Screened

Mid-Level Software Development Engineer specializing in GenAI and full-stack cloud systems

Redwood City, CA5y exp

“Full-stack engineer with experience across Magna, C3.ai, and Amazon, building GenAI-enabled products and finance transaction systems. Has shipped Next.js (App Router) + TypeScript features backed by Go/Python RAG pipelines, and emphasizes production quality via load testing, Selenium regression coverage, LLM-aware integration testing, and Azure observability. Also built LangGraph-orchestrated multi-step content generation workflows with robust retry/idempotency strategies.”

“Seed-stage startup engineer owning features end-to-end across full-stack development, DevOps, rollout, and post-launch maintenance. Built data ingestion and evaluation workflows for an LLM data-quality platform using Next.js, MongoDB, Postgres, and GCP Pub/Sub, with a strong focus on reliability, caching, and pragmatic performance improvements.”

“AI/full-stack engineer with hands-on production experience across React/TypeScript, Go, and Python, spanning an early-stage education startup and a compliance-sensitive internal healthcare data platform. Stands out for shipping LLM and retrieval-based products with measurable impact, including a 27% recommendation improvement, support for 1M+ daily events, and a 19% lift in task completion in a secure, auditable environment.”