Vetted Microservices Professionals

Gilbert Martin

Screened

Executive Cloud Operations & DevSecOps Leader specializing in multi-cloud platforms and compliance

Pleasanton, CA9y exp

“Former founder who built a revenue-generating DevOps GTM service from zero, using milestone-based revenue targets and multi-channel selling (relationships, channel partners, and major conferences like AWS events and Dreamforce). Also led a cross-functional FedRAMP Moderate readiness strategy to enable selling into regulated environments, coordinating engineering/product/finance/sales/security/support and third-party partners under a tight timeline.”

“Built and shipped a production-grade agentic RAG system at CVS Health for patient adherence and medication recommendations, processing 20k+ patient records/day. Strong focus on real-world reliability: hybrid retrieval tuned with re-ranking (<400ms latency), strict JSON/schema validation and tool guardrails, and monitoring/drift detection that reduced MTTD from 6 days to 18 hours while improving recommendation accuracy (+8%) and cutting escalations (~23%).”

Nirmal Attarde

Screened

Mid-Level Software Development Engineer specializing in backend microservices and cloud

3y exp

“Software engineer with Oracle experience deploying a BioCatch fraud-detection integration into HDFC Bank’s core banking platform, using phased rollout and real-time monitoring and reporting ~80% fraud reduction. Also built a modular speech-to-text product (VocalSense AI) achieving ~95% accuracy and has strong production incident response skills (15-minute recovery) plus AWS serverless API hardening for messy inputs.”

“Backend/data engineer with experience at Citi and Elevance Health, building end-to-end pipelines and data services in regulated, high-volume environments. They combine Python, SQL, .NET, Azure Functions, and strong observability/reliability patterns to improve processing speed, reduce manual effort, and maintain high uptime across financial and healthcare data platforms.”

“Backend/AI workflow engineer who built production-grade orchestration systems for hardware security verification at Silicon Assurance (Nextflow/Python/Postgres) and a multi-agent LLM-driven regulatory code checking system at the University of Florida. Emphasizes reliability: strict plan/execute/verify boundaries, queue-based isolation, and strong observability/auditability with Prometheus/Grafana and persisted prompts/tool calls.”

Aidan Anderson

Screened

Director-level engineering leader specializing in AI, security, and FinTech SaaS

California, USA12y exp

“Engineer and bootstrap founder who has worked across roughly five venture-backed startups from pre-seed through Series E. He combines hands-on startup execution with strong judgment around product-market fit, founder fit, and customer validation, while independently building profitable, self-owned micro SaaS ventures on the side.”

“Full-stack product engineer with hands-on ownership across React/TypeScript, serverless backends, and Postgres, combining technical depth with strong UX instincts. Stands out for measurable impact: improved a slow query from seconds to under 200ms and increased onboarding completion by about 25%, while also building reusable platform primitives and scalable multi-tenant configuration systems.”

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.”

Pahuldeep Singh

Screened

Senior Full-Stack Developer specializing in scalable web platforms and automation

Remote6y exp

“Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.”

“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.”

Chanatip Vachirathanusorn

Screened

Entry-level Software Engineer specializing in full-stack and FinTech systems

San Diego, CA2y exp

“Software engineer with AppFolio payments experience who shipped an end-to-end payment adoption rollout during a short internship, including full-stack implementation, stakeholder coordination, and real-time monitoring. Also built an insurance service AI agent inspired by his father's agency, combining structured document ingestion, RAG, and agentic integrations to improve reliability on dense policy documents.”

“ML/LLM systems engineer who has owned AI support automation products end-to-end, including ServiceNow-integrated incident routing, RAG-based resolution suggestion systems, and production stabilization. Stands out for combining hands-on platform work across PySpark, AWS Glue, FastAPI, Kubernetes, and Pinecone with measurable operational impact, including 30-35% MTTR reduction and 25-30% improvement in first-touch resolution.”

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.”

“Engineer with hands-on experience across frontend, backend, and data systems, including React/TypeScript UI work at CitiGroup, ETL pipeline ownership at Accenture, and personal 0→1 builds like an AI chatbot and a real-time multiplayer typing platform. Stands out for combining product-minded prioritization with strong implementation depth in performance optimization, type-safe frontend architecture, and resilient data pipeline design.”

“AI/ML-focused engineer with practical experience building RAG-based and multi-agent systems, including architectures for retrieval, reasoning, context processing, and response generation. Stands out for combining LLM productivity gains with disciplined software engineering practices like validation, monitoring, and reproducibility.”

“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.”

Adithi Anugu

Screened

Mid-level Full-Stack Software Engineer specializing in API and data-driven applications

Florida, USA4y exp

“Full-stack engineer with internship experience at Sports Excitement and AI systems work at the University of Florida, combining React/TypeScript, Node.js, and PostgreSQL with applied AI workflow tooling. Stands out for shipping measurable product improvements—30% faster pagination and 40% higher engagement—and for building observability, eval, and human-review layers around AI-assisted data extraction systems.”

Deepthi Pamisetty

Screened

Mid-level Full-Stack Engineer specializing in FinTech and cloud-native systems

Dallas, TX6y exp

“Full-stack engineer with production experience building AI-powered search and automation systems at JPMorgan Chase and customer-facing product features at Wayfair. Stands out for combining React frontend work with backend microservices, RAG/LangChain AI integration, and cloud-scale performance tuning, including a support chatbot that reduced ticket resolution time by 35%.”

“IBM full-stack engineer focused on document automation for internal and government use cases, building Java Spring Boot services and React/TypeScript UIs that automate XML-to-multilingual PDF workflows. Stands out for turning complex backend automation into usable tools for non-technical operations teams while improving processing speed and reducing manual effort.”

Anshika Bajpai

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Bloomington, IN4y exp

“Engineer with impactful experience at Palo Alto Networks and Optum, focused on production automation and AI-powered internal tools. Built and owned an end-to-end RAG knowledge system adopted by 1000+ internal users with roughly 75% faster response times, and also transformed a legacy Optum coverage-feed workflow from 500+ minutes to under 3 minutes through data standardization and microservices refactoring.”

“Forward-deployed, full-stack/platform engineer who owns production features end-to-end across frontend, backend, data, and infrastructure (AWS serverless, Terraform, React). Has modernized critical fintech/payment systems (zero-downtime monolith-to-microservices with Kafka event sourcing) and productionized AI-native support workflows (LLM + RAG on Pinecone) with measurable gains in latency, incidents, CSAT, and support efficiency.”

“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.”