Vetted API Design Professionals

“Full-stack engineer with experience shipping production features in both networking (Cisco: ACL object groups, 3G/4G) and fintech/online banking (PLAID, Auto Pay, OLB, membership qualification). Works primarily with React/Java/Hibernate and REST/JSON, emphasizing caching/memoization for UI performance and strong testing/XP practices to maintain quality under faster release cycles.”

Harrishkumar Loganathan

Screened

Mid AI/Machine Learning Engineer specializing in FinTech and Generative AI

Remote, USA3y exp

“AI/ML engineer with hands-on ownership of enterprise LLM deployments at Freshworks, including a large-scale RAG chatbot serving 15,000+ users across six departments. Stands out for combining deep production engineering skills—AWS microservices, Kubernetes, observability, retrieval quality, and faithfulness evaluation—with strong cross-functional stakeholder leadership and prior large-scale fraud data pipeline experience at Socure.”

“Built an end-to-end AI resume tailoring system in Python/FastAPI with strong emphasis on reliability, validation, observability, and regression-based quality control. Also demonstrates thoughtful browser and workflow automation skills, especially around brittle UIs, resumable state, and turning ambiguous manual processes into production-ready automated pipelines.”

Saisureshreddy Challa

Screened

Mid-level Data Scientist specializing in AI/ML, LLMs, and domain analytics

California, USA6y exp

“BlackRock AI/ML engineer who built and owned a production LLM document intelligence system for regulatory and investment analysis end-to-end. They combined RAG, multi-agent validation, strong evaluation/monitoring, and reusable Python services to process 50K+ documents, cut review time 40-50%, and improve decision accuracy by about 25%.”

“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.”

“Built and shipped an end-to-end autonomous telemetry and log-triage product that combined LLM-based anomaly analysis, strict typed validation, and a React observability UI. Particularly compelling is their focus on making non-deterministic AI reliable in production at scale—500,000 daily requests and 99.9% uptime—while also translating complex AI output into a usable experience for non-technical teams during live outages.”

“Backend engineer with end-to-end ownership experience on a real-time AI-driven payment authorization/orchestration platform at PayPal. They describe strong fintech systems depth across Java/Spring/Kafka microservices, database and latency optimization, and reliability engineering, with concrete impact including 35% fewer processing failures, latency reduced from 420ms to 140ms, 1,200+ weekly manual reviews eliminated, and 40% faster incident response.”

“Capgemini engineer who helped take a travel insurance platform from prototype demos to a stable production system by clarifying requirements, hardening API contracts, and adding validation/logging to handle real customer data and external integrations. Experienced in real-time troubleshooting of complex workflows (including LLM/agentic-style workflows) through strong observability practices, and in leading practical developer-focused demos that accelerate client integration and adoption.”

“Engineer with banking and industrial/IoT experience who has deployed a payment-processing microservice with zero downtime, handling Protobuf schema evolution and sensitive data migration via dual-write/checksum techniques. Demonstrates strong cross-stack troubleshooting (pinpointed intermittent distributed timeouts to a failing ToR switch port) and customer-facing Python ETL customization using plugin-based parsers and Pydantic validation, plus hands-on monitoring/alerting improvements with operators.”

“Backend-focused engineer who built a Python/Flask task-management API with JWT/RBAC, modular service/repository architecture, and PostgreSQL/SQLAlchemy performance optimizations (indexes, lazy loading, bulk ops, pooling). Also implemented multi-tenant data isolation strategies and built an OpenAI-powered document summarization workflow using chunking, async processing, Redis background workers, and caching to improve throughput.”

“Engineering leader/player-coach who helped ship a web-based ERP SaaS release (Nov 2025) as part of a long-term migration from a legacy desktop ERP, designing a multi-API architecture (Oracle + EF Core, caching, integrations) and enforcing rigorous code review quality gates. Previously led development of a low-latency, multi-service high-frequency trading platform at a startup hedge fund (Capitalogix Trading), leveraging async/multithreading, event-driven messaging, NoSQL, and WebSockets.”

“Full-stack engineer with end-to-end ownership experience, including building a real-time campaign/inventory dashboard at P&G using React/TypeScript, Spring Boot, GraphQL/REST, Redis, Docker, and AWS (EC2/RDS/S3) with Prometheus/Grafana observability. Demonstrates strong performance and reliability focus (p95 tuning, caching, idempotent event-driven ingestion with DLQs/reconciliation) and has shipped MVPs in ambiguous early-stage environments.”

Srinivas Matta

Screened

Mid-Level Full-Stack Software Developer specializing in cloud-native web platforms

Paducah, KY4y exp

“Software engineer at Capital One who owned and shipped AI-driven personalization and internal insights dashboards end-to-end, emphasizing fast iteration with feature flags and tight user feedback loops. Built a TypeScript/React + Spring Boot/Python document automation platform with compute-heavy NLP microservices, async workflows, and production-scale reliability/performance practices (Kafka/RabbitMQ-style queues, Redis caching, tracing).”

SAI RAKAM

Screened

Mid-Level Software Engineer specializing in backend microservices and FinTech payments

Remote, USA3y exp

“Capital One engineer focused on fraud and payments platforms, owning end-to-end services and internal tools used by fraud analysts. Built high-traffic Kafka/REST systems and real-time React/TypeScript dashboards (WebSockets, Redis), with strong emphasis on observability, idempotency, and scalable microservices. Successfully drove adoption of AI-assisted fraud classification by pairing transparency and manual overrides with measurable workflow improvements.”

Shangyi Chen

Screened

Mid-Level Full-Stack Software Engineer specializing in Java and Angular web applications

San Francisco, CA5y exp

“Full-stack engineer who has owned end-to-end delivery of an internal, customer-facing data visualization product and helped build a data modification pipeline used across the organization for data integrity/governance. Demonstrates pragmatic MVP-driven delivery within sprints and makes performance-oriented architectural decisions (e.g., batching API calls to reduce frontend request volume) in TypeScript/React systems.”

Suloni Praveen

Screened

Entry-Level Software Engineer specializing in data engineering and ML systems

Los Angeles, CA0y exp

“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”

“Product-minded full-stack engineer with deep experience building React/TypeScript + serverless/SQL systems and improving both operational reliability and user activation. They stand out for connecting low-level architecture decisions like idempotency and atomic updates with business outcomes such as reduced support burden and lower 30-day cancellations, while also designing configurable multi-tenant product systems with strong guardrails.”

Amit Dharam

Screened

Junior AI/ML Software Engineer specializing in backend systems and cloud deployment

Tempe, AZ3y exp

“Built multiple end-to-end automation and data systems, including an Accio RAG pipeline combining PDF parsing, FastAPI, Neo4j, and vector search, plus Selenium-based scraping for a virtual try-on product. Stands out for reliability-minded engineering: automated testing, structured logging, validation layers, and a data-driven approach to debugging flaky automation that improved CI pass rates to over 98%.”

“Full-stack product engineer who has built end-to-end apps and internal tools spanning React/TypeScript, Node/Express, and Postgres. Stands out for pragmatic shipping under ambiguity, creating reusable platform primitives like a centralized notification API, and designing safe multi-tenant configurable dashboards with schema validation.”

“Product-minded full-stack engineer who has built AI-heavy systems spanning Next.js/TypeScript frontends, Python/FastAPI backends, queues, databases, and workflow infrastructure. Stands out for combining strong technical depth with UX instincts—improving trust in AI assistants, shipping ambiguous client features quickly, and creating reusable primitives for AI generation and analysis products.”

“UC Berkeley CS–trained hands-on engineering leader with executive experience spanning fundraising and board/customer communication. Led architecture and roadmap for AI-driven fintech platforms (including portfolio data, market signals, document processing, and Bitcoin trading), scaling global orgs (~100 people) and driving modular API-based designs that improved reliability, onboarding speed, and customer retention.”

“Senior product leader with experience across Times Internet, Mudah.my, Wells Fargo, and delivery/logistics products, spanning SaaS, marketplace, fintech, and AI-enabled platforms. Stands out for building products end-to-end with strong commercial outcomes, including a multi-channel engagement platform that became a new SaaS revenue stream and AI features that improved marketplace liquidity while keeping humans in control.”

“Veteran software engineer with an unusual path from founding a game development company and shipping dozens of games to rebuilding a B2B product data platform after bankruptcy reduced engineering to a two-person skeleton crew. Particularly strong in legacy modernization, data synchronization, enterprise UI/backend architecture, and customer-safe migrations where old and new systems must coexist in production.”