Vetted API Integration Professionals

“Built internal product features at Sysco's Collab Cafe across React/TypeScript frontend and Spring Boot/PostgreSQL backend, including a full project invite flow and an early AI-style project matching capability. Stands out for owning features end-to-end, improving React dashboard performance with profiling and component refactoring, and making pragmatic 0→1 tradeoffs to ship quickly.”

Neeshma Narahari

Screened

Mid-level Software Developer specializing in backend microservices and cloud platforms

Irving, TX6y exp

“Full-stack product engineer with strong React and TypeScript depth who has owned dashboard features end-to-end, from UI architecture and rendering optimization through Spring Boot APIs and database query tuning. Particularly compelling for startup or high-growth teams: they’ve shipped 0→1 internal operations platforms, prioritized MVP workflows effectively, and iterated post-launch using user feedback, logs, and usage metrics.”

“Python backend engineer with experience combining traditional API/microservices development and GenAI integrations, including healthcare claims workflows. Particularly compelling for teams building production AI systems: they pair hands-on work with LLMs, RAG, LangChain-style orchestration, and AWS deployment with a strong emphasis on reliability, security, and engineering discipline.”

Ming Wang

Screened

Entry-level Software Engineer specializing in AI and FinTech

Hong Kong, Hong Kong1y exp

“Recent college graduate and software engineer who relies heavily on AI-assisted development, reporting that roughly 85% of code in a recent initiative was AI-generated and then manually reviewed. Has built customer-facing AI features including personalized recommendations and an internship chatbot tied to product advertising, with exposure to API communication, database checks, and conversation monitoring.”

“Software engineer with Intuit experience shipping an end-to-end real-time financial insights product on AWS, using event-driven architecture with Kafka and Spark Streaming to process millions of records with low latency. Also delivers customer-facing React + TypeScript dashboards and has hands-on production operations experience, including resolving a database scaling incident via read replicas, query tuning, and connection pooling.”

“Built and deployed a production LLM/RAG document automation system for business documents (contracts/claim forms) that extracts schema-validated JSON, generates grounded summaries/Q&A, and integrates into transaction systems via APIs. Emphasizes real-world reliability: hallucination controls, layout-aware parsing with OCR fallback, Step Functions-orchestrated workflows with retries/timeouts, and human-in-the-loop review designed in close partnership with operations and claims stakeholders.”

“Backend engineer focused on Python/FastAPI microservices, with hands-on experience deploying to AWS (EKS/ECR) via Jenkins and GitOps-style workflows using ArgoCD. Has built and stabilized real-time Kafka payment-event streaming pipelines and improved production performance under peak load through Redis caching, SQL optimization, and robust retry/DLQ patterns. Also supported phased migrations from on-prem environments to AWS with gradual traffic shifting and monitoring.”

“Built and shipped a production LLM-powered healthcare support agent at UnitedHealthGroup, using LangChain + FAISS RAG on AWS SageMaker with CloudWatch monitoring and human-in-the-loop fallbacks for safety. Strong focus on reliability engineering (confidence gating, retries/timeouts, caching) and continuous evaluation loops; reported ~40% improvement in query resolution efficiency while reducing manual support workload.”

Zuocheng Li

Screened

Entry-Level Software Engineer specializing in full-stack web and Android development

San Jose, CA0y exp

“Early-career developer whose experience comes from classroom projects but has completed full end-to-end web app delivery: implemented login/search/favorites, integrated external APIs, and deployed to Google Cloud for multi-device use. Demonstrates user-centered iteration by recruiting friends to test and provide feedback, and has hands-on production-style debugging experience (e.g., resolving CORS issues during deployment).”

Ganesh Bandi

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and MLOps

USA6y exp

“LLM engineer who has deployed production RAG systems for regulated document QA (PDFs/knowledge bases), emphasizing grounded answers with citations, RBAC, monitoring, and continuous feedback. Demonstrates deep practical expertise in retrieval quality (semantic chunking, hybrid BM25+embeddings, re-ranking), reliability (guardrails, deterministic workflows), and measurable evaluation (golden sets, log replay, A/B tests) while partnering closely with compliance/operations stakeholders.”

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.”

“Salesforce-focused candidate with hands-on experience owning Sales Cloud automation end to end, including requirements translation, Flow/Apex design, testing, and production deployment. They show practical judgment in choosing hybrid declarative/code solutions, bulk-safe Apex patterns, and modern UI work across both LWC and legacy Aura components.”

Chaitanya Prasad Reddy Narala

Screened

Mid-level AI/ML Engineer specializing in FinTech risk and fraud systems

USA4y exp

“Senior AI/ML engineer focused on production LLM systems, combining RAG, fine-tuning, distributed training, and AI safety to ship scalable real-time moderation and conversational AI platforms. Stands out for pairing deep AWS/Kubernetes MLOps expertise with measurable impact: 40% lower latency/cost, 30-50% fewer hallucinations, and major reliability gains through observability and automation.”

Farhan Shahbaz

Screened

Senior Software Engineer specializing in cloud infrastructure and platform engineering

New York, NY4y exp

“Backend engineer with deep experience in security and access-management platforms at JPMorgan Chase, including owning automation for migrating 50+ engineering teams from CyberArk to HashiCorp Vault. Stands out for combining regulated-environment rigor, infrastructure automation, and production operations with practical AI integration in internal access workflows.”

“Product designer with hands-on front-end implementation experience who has owned complex flows end-to-end at Wix and Intuit, including a live keynote demo for Wix’s first developer conference and a tournament-based inner-source readiness program across global AI/data teams. Particularly strong at turning ambiguous briefs into structured experiences, using design systems rigor, interaction design, and implementation fluency to ship polished, understandable products.”

Sanjay Santhanam

Screened

Mid-level AI Software Developer specializing in backend and LLM applications

San Jose, CA3y exp

“Backend/AI systems engineer focused on productionizing agentic document-processing workflows for large financial PDFs. They describe owning deployments end-to-end, combining Python, Redis, LLM function calling, RAG/ReAct-style orchestration, and strong reliability practices to deliver 80% faster processing, reduce parsing errors from 12% to ~1%, and sustain 99.9% uptime in high-concurrency environments.”

“GenAI/ML engineer from Lucid Motors who built and productionized an LLM-powered RAG diagnostic assistant for manufacturing and maintenance teams, deployed on AWS with Docker/Kubernetes and MLflow. Demonstrates end-to-end ownership from retrieval/prompt design to scalability, monitoring, and workflow integration via APIs, plus production ML pipeline orchestration with Kubeflow (Spark/Kafka + TensorFlow) for predictive maintenance use cases.”

“Research-focused AI engineer who built an agentic pipeline to automatically extract Sphinx-based API documentation/changelogs and generate synthetic tasks for a dynamic LLM code benchmark targeting real-world API evolution and deprecations. Experienced with multi-agent orchestration (AutoGen, LangChain, CrewAI) and rigorous evaluation methods, and has prior multi-agent work from a Microsoft Research internship.”

“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.”

“AI engineer with robotics perception experience at Forterra, building and deploying moving-object/obstacle detection models into real-time robot pipelines. Addressed training crashes/latency via sub-batch training and optimizer tuning, and improved debugging using ROS/ROS2 tooling with 3D voxel visualization and color-coded validation.”

“Data engineer with experience delivering an end-to-end pipeline handling ~3.5TB in a star-schema setup (fact + dimensions) and producing business-facing tables in Hive/Spark. Identified and resolved UAT-reported duplicate issues caused by joins through root-cause analysis, and also built automation to run Spark SQL metrics on weekly/monthly/quarterly cadences and distribute results to users.”

Subbu Paravatareddy

Screened

Engineering Leader specializing in cloud modernization and AI/ML integration

Emeryville, CA21y exp

“Player-coach engineering leader focused on buyer/distribution product lines, building scalable purchasing/planning frameworks and modernizing workflows. Drove performance and reliability improvements via queue-based async architectures, external API redundancy, and CI/CD automation, and has led production incident response (cache-related) with follow-up playbooks and monitoring. Experienced in high-growth/startup environments, combining hands-on delivery with mentoring, 1:1s, and performance coaching.”

Corey Bowlby

Screened

Executive Product & Technology Leader specializing in FinTech SaaS, core banking, and payments

Abu Dhabi, United Arab Emirates23y exp

“Product/technology executive who has repeatedly built and scaled engineering organizations from early-stage startups to large enterprises (including Temenos with ~2,000 developers). Led major platform modernizations (monolith-to-microservices) to enable SaaS, resilience, and faster delivery, and launched an innovation hub to build proprietary neural-network biometric algorithms for a payments product enabling "wave of the hand" transactions.”