Vetted Microservices Professionals

Sankalp Tiwari

Screened

Mid-Level Software Engineer specializing in backend microservices and FinTech data pipelines

New York, NY4y exp

“Backend engineer at Goldman Sachs who built LLM-powered reconciliation/reporting services and high-throughput Kafka pipelines (8M+ events/day). Strong in production-grade Python/FastAPI microservices on Kubernetes with GitOps-style CI/CD, plus experience migrating legacy reporting/settlement services onto an internal Kubernetes platform using shadow deployments and gradual cutovers.”

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.”

Atharva Bhide

Screened

Entry Software Engineer specializing in AI/ML and multimodal systems

Los Angeles, CA1y exp

“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”

“Built a production Python microservice around Grafana Loki focused on reliability, with checkpointing, idempotency, replay tooling, tracing, and alerting to prevent data loss and silent lag. Also has hands-on experience hardening brittle Playwright automations against dynamic UIs, auth expiry, rate limits, MFA, and bot-detection constraints, plus turning tribal-knowledge SOPs into explicit state-machine-driven workflows.”

Ramesh Namperumal

Screened

Executive technology leader specializing in AI/ML, data engineering, and enterprise architecture

Alpharetta, GA27y exp

“Technical founder building an AI IT helpdesk agent startup, currently leading product development as acting CTO/CPO and doing much of the development personally with a small partner group. Brings years of cross-industry technical experience, product/vendor evaluation expertise, and a deliberate strategy to delay outside capital until the product and customer traction are stronger.”

“Data-engineering-oriented candidate with hands-on experience building an agentic AI product and operational automation workflows. They described automating inventory-to-ERP discrepancy reconciliation with anomaly detection and daily reporting, and also have practical scraping/automation experience dealing with Cloudflare-protected sites using Selenium and Puppeteer.”

Francois Odienne

Screened

Director of Engineering specializing in SaaS platforms, AI-first product development, and telecom

Moorpark, CA28y exp

“Technology leader with venture-backed company experience at LogicMonitor, where they aligned engineering strategy with business growth and long-term platform scalability. Demonstrates strong familiarity with the VC/studio/accelerator ecosystem and a thoughtful founder mindset centered on validating real problems, innovative solutions, and execution capacity.”

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%.”

“Backend/product-minded engineer from Ramp with strong travel-tech experience, having built an end-to-end booking platform integrating multiple external providers, policy enforcement, and reporting infrastructure. They also shipped an LLM-powered personalization workflow using embeddings and Google Gemini that cut trip planning time by 22%, and demonstrated strong production reliability instincts through circuit breakers, health checks, and schema-driven normalization.”

“AI/ML engineer who has built a production text-to-image generation system in PyTorch with an AWS-backed inference setup, focusing on GPU-efficient training and embedding-space architectural choices inspired by recent research (e.g., Meta VL-JEPA). Uses both metric-based evaluation (FID) and human testing to validate real-world visual quality, and can translate technical concepts for non-technical stakeholders.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

“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.”

“Full-stack engineer with enterprise banking experience at Citi and hands-on production AI agent work, including a multi-agent incident analysis pipeline using LangGraph, RAG, and LangSmith. Also built a zero-to-one healthcare operations dashboard spanning hospital workflows and AI-assisted clinical features, suggesting a blend of strong systems engineering and product-minded execution.”

Keerthi Pericherla

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech applications

Remote, USA5y exp

“Frontend engineer with HCL Tech experience building loan operations dashboards and React/TypeScript data-heavy interfaces. Stands out for combining maintainable component architecture with hands-on performance tuning, including a reported 30% load-time improvement in a production visualization-heavy application.”

PrabhjyotKaur Bamrah

Screened

Mid-level Full-Stack Software Engineer specializing in enterprise apps and AI/ML

Redwood City, CA4y exp

“Engineer with experience scaling enterprise AI products in production, including a C3 AI deployment expanded from 2 to 4 sites across the US and Canada. Also built a GPT-4o-powered RAG assistant for plant operators, combining structured and unstructured data with human-in-the-loop safeguards and iterative evals to improve answer quality.”

“Frontend-focused product engineer with experience at IBM and Intel building internal enterprise platforms, especially incentive and employee operations workflows. They repeatedly describe owning both UX/design decisions and the React frontend implementation, with strong emphasis on reusable components, API integration, and shipping ambiguous workflow products into production.”

“Founding Principal Engineer/Head of Engineering at Amberflo (Seed $5M Homebrew; Series A Norwest) who built and shipped an AI Gateway + real-time LLM cost metering/pricing MVP end-to-end (control plane/data plane, AWS infra, CI/CD). Known for extremely fast MVP cycles (often 1–2 weeks), scaling teams (50–60 hires), and driving major pivots (usage-based billing to FinOps) by repurposing an existing metering/pricing platform; based in Chicago and has led a Silicon Valley startup remotely with frequent Bay Area travel.”

“Software engineer with strong end-to-end ownership of search and listing systems (React/TypeScript frontend with Node.js + Spring Boot backends), focused on shipping fast while managing risk via feature flags, testing, and metrics. Demonstrated measurable UX/performance wins (reduced latency and search abandonment) and built internal observability tooling (dashboard + alerts) that improved incident response. Experienced with microservices reliability patterns including idempotency and dead-letter queues.”

“Software engineer with Capital One experience contributing to shared internal “open-source style” JavaScript/React/TypeScript libraries (component library and hooks/utilities). Drove measurable performance gains (~25% improvement) by refactoring hooks to prevent unnecessary re-renders, and improved adoption via stronger documentation, testing (Jest), semver discipline, and code review/PR workflows; also stabilized a backend service by adding monitoring and automated tests in an unstructured project.”

“Built a production internal RAG-based Q&A assistant at Huawei for ~4,000 engineers over a 12M-document Elasticsearch corpus, replacing link-only search with synthesized answers and achieving 87% user acceptance while keeping hallucinations under 0.4%. Pairs rigorous offline benchmarking (RAGAS, PR-gated F1 improvements) with human A/B testing and OpenTelemetry-based production monitoring, and also has strong Kubernetes/SRE experience orchestrating 50+ gRPC services with major MTTR and pager-fatigue reductions.”

“Backend engineer focused on building production-ready Python services (Flask/FastAPI) with strong performance and scalability instincts—Celery/Redis background processing, robust multi-tenant isolation (Postgres RLS), and pragmatic CI/Docker operations. Demonstrated measurable DB optimization impact (cut a critical analytics query from ~1–2s to ~100–150ms) and has hands-on experience integrating LLM/ML workflows (OpenAI, LangChain, embeddings, Redis/FAISS vector stores) without degrading API responsiveness.”

“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”

“Backend/DevOps-focused engineer with healthcare and financial systems experience, including an ICU readmission risk platform delivering real-time ML scores via a secure FastAPI service (PyTorch model serving, PostgreSQL, Celery/Redis) deployed on AWS with strong observability. Has hands-on Kubernetes GitOps delivery (Helm, ArgoCD, HPA) and has supported a JPMC on-prem-to-AWS microservices migration using phased validation and blue-green cutovers, plus Kafka/Avro streaming for real-time transaction processing.”