Vetted API Development Professionals

Amaan Elahi

Screened

Mid-level Software Engineer specializing in backend, AI, and full-stack systems

New York, NY5y exp

“Built and shipped production LLM agents including an internal RAG-based compliance classification system at SAIL (FastAPI/Redis/Docker) designed to handle real failure modes and scale to ~10k LLM calls/hour, achieving ~93% pipeline accuracy with reduced hallucination risk via multi-model orchestration and strict grounding. Also architected “Elara,” a state-machine-driven conversational appointment booking agent using structured JSON outputs and backend function execution for reliability, and has experience normalizing messy OTA/PMS data at RateGain.”

“Unity/C# game engineer with about 3 years of experience who owned a high-impact runtime content delivery platform at Zynga/Singa powering LiveOps releases for roughly two years. Their work cut app size by 35-40%, removed a 25K daily activator drop on release days, improved load times by 25%, and supported a feature that drove 10% quarterly revenue growth.”

“Built Bargain Bricks end-to-end as a solo creator, handling product ideation, design, backend, APIs, website, and native iOS/Android apps. They actively maintain and iterate on the product, which has over 1,000 downloads, and have improved conversion through UI changes that surfaced the best deal above the fold.”

Malyadri Peruru

Screened

Senior Software Engineer specializing in backend, cloud, and IoT automation

Greater San Francisco, CA13y exp

“Software engineer with strong systems design experience spanning both core product infrastructure and AI-enabled support workflows. Co-led a from-scratch B2B SaaS billing platform for complex customer pricing models, and also improved an orchestrated agent system by tightening context, metadata, and human-review safeguards for misrouted support tickets.”

“Engineering leader with experience owning product engineering strategy, architecture, and org scaling across hospitality/workforce management and insurance startup environments. They describe being brought in to help Fourth Inc. revamp engineering for large-scale enterprise customers, while also scaling teams at The Zebra and staying hands-on with production monitoring, performance analysis, and cross-team architectural execution.”

“Software engineer with hands-on embedded/robotics coursework experience (Arduino sensor integration and input handling built from scratch without external libraries) and strong DevOps/engineering productivity impact at work, including leading a CI/CD enhancement that runs only impacted tests to catch issues before PR approval.”

“Backend/founding-engineer-style builder who designed and evolved a near-real-time customer churn prediction platform (FastAPI + AWS SageMaker/Lambda + Redis + MLflow) to enable real-time retention actions, reporting ~18% churn reduction. Demonstrates strong production engineering in secure API design, incremental migrations with data integrity safeguards, and robustness improvements in async pipelines (idempotency, DLQs, retry visibility).”

“Robotics-focused candidate with multiple university robotics projects (MTE 380, MTE 544) and ROS 2 (Humble/Galactic) experience spanning perception, navigation, and simulation. Built a vision-based line-following and retrieval robot using HSV filtering and homography, and debugged real-time PID overshoot issues via timestamping/rate-limiting. Comfortable with distributed ROS 2 architectures (Python perception + C++ control), DDS/QoS, Gazebo testing, and Dockerized deployment.”

“Robotics software engineer/researcher with hands-on real2sim experience for deformable manipulation: led real-world data collection and diffusion policy deployment on an Aloha robot, then built a MuJoCo + Gaussian-splat digital twin with point-cloud alignment. Also brings 3 years of production software engineering experience, including Docker/CI/CD and a zero-downtime Blue-Green upgrade of a core API router, plus ROS/ROS2 work spanning autonomous vehicles and UR20 pick-and-place with MoveIt2.”

“Built and deployed custom AI chatbots at LivePerson, translating customer service pain points (e.g., MTTR reduction and fragmented information) into production RAG-based solutions with stakeholder-facing metrics dashboards. Experienced in real-time troubleshooting using Elastic logs, leading POCs, and integrating customer APIs to automate workflows as part of sales-driven solutioning.”

“LLM/RAG engineer who has shipped production systems in high-stakes domains (fraud analytics at Mastercard and security compliance as a CI/CD gate). Strong focus on reliability: hybrid retrieval for latency, citation-backed outputs for trust, and code-driven eval/regression pipelines using golden datasets. Also built scalable OCR-based ingestion for messy classroom artifacts (handwriting, PDFs, whiteboard photos) using Go/Python and cloud services.”

Ajay Madhusudhan Thumala

Screened

Junior Software Engineer specializing in data engineering and LLM applications

Irvine, CA1y exp

“Computer science engineer and master’s graduate who independently built a mechatronics-heavy capstone prototype: a smartphone concept for deafblind users using micro-actuator arrays for braille reading. Also has platform engineering experience at Quantiphi, deploying webhooks to Kubernetes and implementing GitOps-based CI/CD using AWS CodeCommit/CodeBuild and ECR.”

“5-year .NET full stack developer who has applied AI-assisted development in an enterprise Cisco environment, using tools like GitHub Copilot and ChatGPT to accelerate microservice API delivery while maintaining architecture, security, and code quality standards. Notably reports a roughly 30% reduction in development time on a customer policy management/claims processing project through disciplined use of AI for boilerplate, testing, and design validation.”

“Built and stabilized an AI-assisted document processing workflow for Possible Finance that supported underwriting without automating final loan decisions. Stands out for combining practical LLM integration skills with strong guardrails, validation, and fallback design in a financial workflow, delivering roughly a 35% reduction in document processing time.”

“UPenn robotics researcher who architected a real-time autonomous driving decision-making engine, integrating LSTM trajectory prediction with MPC in CARLA and adding conformal prediction to deliver 95% statistical safety guarantees under strict latency constraints. Also built and debugged an autonomous quadrotor stack with ESKF-based 6-DoF tracking and optimized A*/Dijkstra planning to eliminate latency-induced instability, with experience bridging heterogeneous simulation/control systems.”

“Software developer with healthcare operations experience at Epic Systems (Referrals & Authorizations), delivering customer-facing tooling to speed manual insurance authorization/denial documentation and support future automation. Also supported an HRIS migration to Workday at Aloe Yoga, solving legacy ID interoperability via scripting and mapping, and demonstrates strong production debugging and test-driven maintainability practices.”

“Cornell master’s student (CS/Stats) focused on research-heavy ML projects: implemented a sparsity-driven RL approach (DAPD + Soft Actor-Critic) that maintained stable learning even with ~95% of weights removed in OpenAI Gym continuous-control tasks. Also worked on diffusion-based computer vision with conditioning and latency-focused U-Net choices, and scaled unsupervised community detection on a 50k-node/800k-edge Reddit graph via BFS subgraph sampling.”

John Chen

Screened

Junior Full-Stack & Data Scientist specializing in ML/NLP and analytics products

Redwood City, CA2y exp

“Built and deployed profitprops.io, a sports betting player-props prediction product using ML/AI. Implemented backend APIs with FastAPI/Express.js and Supabase, trained models on AWS GPU (P3) using Docker + RAPIDS, and set up CI/CD with GitHub Actions while working around cost constraints and data-collection hurdles (EC2 proxy rotation/rate limits).”

Junhui Huang

Screened

Intern Machine Learning Engineer specializing in LLMs, MLOps, and NLP

Providence, RI1y exp

“Built and deployed a production LLM-driven Dungeons & Dragons game where the model acts as a dungeon master, adding a structured combat system and a macro-state tree to ensure campaigns converge to a clear ending. Fine-tuned Gemini 2.5 Flash on Vertex AI and deployed on GCP with Kubernetes, using RAG over DnD rules/spells plus multi-agent orchestration (intent-based routing between narrative and combat agents) to reduce hallucinations and improve reliability.”

Belal Beydoun

Screened

Intern Full-Stack Software Engineer specializing in AI and data analytics

Detroit, MI2y exp

“Software engineer focused on real-time, low-latency AI pipelines: built an end-to-end mobile-to-backend image classification system using React Native/Expo, Node.js, gRPC, MySQL, and Google Vision AI, optimizing throughput and latency. Also integrated an AI model into a real-time field workflow at DTE via Node.js + Azure Databricks, adding data cleaning/validation and safe fallback logic for reliability in operations.”

Aditya Jaiswal

Screened

Intern Software Engineer specializing in cloud, DevOps, and applied AI

Carlsbad, CA1y exp

“Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.”

Michael Cohen

Screened

Executive Data & AI Leader specializing in enterprise SaaS and marketing analytics

New York, NY17y exp

“AI strategy and execution consultant currently doing contract/ad hoc work and planning to formalize the business with partnerships, GTM strategy, pro forma financials, and marketing/tech investments focused on AI productivity, governance, and security. Background includes founding startup teams, M&A/integration, and operating leadership in VC-backed scale-ups (Insight Ventures, EIP, Zetta Ventures) plus C-suite experience in a global PE-backed holding company, with 20+ years of published work in prediction and decision systems.”

“AI/LLM engineer with strong healthcare domain depth who has shipped production-grade agents for care coordination and clinical workflow automation. Stands out for combining Knowledge Graph RAG, LangGraph orchestration, and rigorous eval/guardrail systems to improve reliability in high-stakes environments, with measurable gains in review time, hallucination reduction, latency, and clinician adoption.”