Vetted Distributed Systems Professionals

“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”

“Systems Engineer at Tata Consultancy Services with hands-on ownership of enterprise logistics microservices (Spring Boot) using Kafka integrated with Azure Event Hubs, including partitioning strategies and operational handling of consumer lag/duplicate events. Also built a full-stack road-accident blackspot detection application using Python-based spatial clustering and model evaluation with a JavaScript/Mapbox frontend.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“Software engineer with experience at Wipro Technologies and Wells Fargo building React-based SPAs, reusable component libraries, and developer documentation. Demonstrated strong performance engineering (React.memo, list virtualization, code splitting) with reported >50% rendering-time improvement, plus hands-on production support by diagnosing API outages via monitoring/logs and implementing traffic/server fixes. Comfortable leading workstreams in fast-changing environments using Kanban and tight stakeholder feedback loops.”

“Software/ML engineer who built a production automated job-finding and cold-email personalization system for Fortune 500 outreach, using JobSpy for dynamic scraping, LangChain orchestration, and LLM+vector DB semantic search with grounding/relevance metrics and guardrails. Also delivered a predictive investment analytics platform for financial advisors, communicating results via Tableau dashboards and portfolio KPIs like Sharpe ratio and drawdowns.”

“Backend/platform engineer with State Farm experience modernizing and scaling an enterprise consolidated payment data platform and event-driven pipelines. Built cloud-native payment architecture (ECS->EKS) handling millions of financial transactions/day and high-volume telemetry (~100M events/day), with strong schema governance (Avro + schema registry) and production operations/incident mitigation driven by observability.”

“Built and shipped a production LLM-powered customer support agent for an EV charging platform using RAG plus internal APIs, automating session/payment issues and ticket routing. Emphasizes production readiness via guardrails, schema validation, state-machine orchestration, monitoring, and continuous evals, delivering a reported 35–40% reduction in support tickets and improved customer satisfaction.”

Piyush Rajendra

Screened

Mid-level AI/ML Engineer specializing in production RAG systems and MLOps

Athens, GA4y exp

“Built and deployed a GPT-4 + Pinecone RAG system that lets users query large internal document collections with grounded, cited answers. Demonstrates strong applied LLM engineering (chunking experiments, hallucination controls, metadata recency boosting) plus production-minded evaluation/monitoring and performance tuning (rate-limit mitigation via pooling/batching). Also effective at translating complex AI concepts to non-technical stakeholders through prototypes and live demos, helping secure client sponsorship.”

Hrishi Kamal Earla

Screened

Senior Full-Stack Java Developer specializing in cloud-native FinTech microservices

Remote, CA7y exp

“JavaScript/React engineer with hands-on open-source library contribution experience, including thoughtful PRs that improved error handling, API flexibility, and added features backed by tests and documentation. Demonstrates a profiling-first approach to UI/runtime performance (memoization, component splitting, render-path optimization) and strong community support skills—reproducing edge cases, delivering sustainable fixes, and communicating workarounds and releases.”

Manali Patil

Screened

Senior Software Engineer & Engineering Manager specializing in cloud backend and manufacturing MES

Santa Clara, CA9y exp

“Customer-facing engineer who led recurring midnight ERP data-feed/B2B integrations from prototype to production, building reusable APIs and using Hangfire for job scheduling. Known for tight weekly customer iteration, strong documentation and test coverage (80%+), and cross-functional problem-solving with Operations/Quality/NPI to resolve data-collection and manufacturing-process constraints; has 2 customers live on the integration.”

Serge Ahranovich

Screened

Executive CTO / Platform Architect specializing in IoT, telematics, and EV charging infrastructure

Los Angeles, CA20y exp

“Founder of TimeTick (timetick.io), an AI-powered diagnostics platform for IoT combining device simulation, automated testing, and real-time monitoring—initially focused on EV charger diagnostics. Former VP of Engineering with a track record of building IoT systems from scratch and applying AI to detect protocol-failure patterns that drive downtime; currently supporting existing customers and converting pilots (with leads like Siemens and ABB) into paid subscriptions.”

“Full-stack product engineer with hands-on experience shipping React/TypeScript applications on AWS serverless infrastructure with Postgres. Stands out for combining measurable performance optimization (~30% faster APIs), UX improvements that lifted activation by 25%, and pragmatic platform thinking through reusable hooks and safe multi-tenant dashboard customization.”

“Full-stack/AI engineer who has shipped production systems spanning real-time analytics dashboards and an internal LLM-powered knowledge assistant. Experienced with RAG pipelines (embeddings/vector DB, semantic retrieval, query rewriting) plus evaluation loops and guardrails, and builds observable Kafka-based data pipelines monitored with Prometheus/Grafana.”

Harshitha Ayenugula

Screened

Mid Software Engineer specializing in backend and FinTech systems

New Jersey, USA4y exp

“Full-stack engineer with strong ownership of complex web products, including building a real-time collaborative editor end-to-end using React, Spring Boot, WebSockets, Yjs CRDT, PostgreSQL, Redis, and Docker. Stands out for combining product delivery with production reliability and performance work, including reducing QA defects by ~25%, improving internal tool load times to under 2 seconds, and resolving latency issues in live systems.”

Surya Padmini Konjula

Screened

Mid-level Software Engineer specializing in backend, cloud, and AI for FinTech

San Jose, CA6y exp

“Senior full-stack engineer focused on AI-powered workflow automation and customer support products, with hands-on ownership from React/TypeScript UI through FastAPI microservices, retrieval pipelines, and Kubernetes deployment on GCP. Particularly strong in turning ambiguous zero-to-one AI initiatives into production systems that reduce manual operations, improve turnaround time, and remain reliable through strong orchestration and monitoring practices.”

“Backend and distributed-systems engineer with experience integrating LLM capabilities into clinical data workflows at CVS. Stands out for treating AI as an engineering accelerator rather than a shortcut, with strong emphasis on validation, observability, Kafka-based async pipelines, and safe multi-agent orchestration for production systems.”

“Senior product leader who helped transform Submittable from a single-program grant tool into a multi-program impact platform, driving ARR from $20M to $70M+ while improving retention and margins. Particularly strong in enterprise platform strategy and human-centered AI, with a clear philosophy of using AI to augment expert judgment rather than replace it.”

“Built and shipped a production LLM-driven data harmonization/record-matching pipeline for pharmaceutical datasets, combining normalization, embeddings/vector search, and an LLM validation step. Emphasizes production reliability via guardrails, confidence thresholds, idempotent/retryable stages, and human-in-the-loop fallbacks, with monitoring focused on manual review and error rates to reduce false positives.”

“Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).”

“AI/ML engineer with experience at Northern Trust and Persistent Systems building production LLM + RAG systems for regulated financial use cases, including liquidity forecasting, anomaly detection, and credit scoring. Emphasizes compliance-first design with explainability (SHAP), traceability (MLflow), and hallucination controls (FAISS + citation-grounded prompting), and has delivered drift-triggered retraining pipelines using Airflow and Kubernetes while translating model outputs into business-ready marketing segments.”

“Full-stack engineer who has owned React/TypeScript + Spring Boot dashboard products end-to-end, including real-time performance/alerts and data aggregation across services. Strong in shipping MVPs quickly with feature flags, automated testing and CI/CD, and using monitoring/click-path analytics to prioritize work—achieved a 40% page-load reduction. Experienced operating microservices with RabbitMQ at scale, addressing retries/idempotency/observability and fixing duplicate-processing incidents with idempotent consumer patterns and DLQs.”

“Engineering leader with a strong automation-first philosophy ("special treatment doesn't scale"), experienced in building self-service tooling and communicating clearly with executives via BLUF-style updates. Has delivered end-to-end business-driven solutions—from sourcing alternative vendor data to installing infrastructure and writing drivers/analytics—and led pragmatic architecture changes in R/Rserve that significantly improved performance while driving cloud costs toward near-zero.”

“Built and shipped an AI-driven interview evaluation pipeline at SeekOut that automated recruiter screening via a multi-stage LLM agent workflow (.NET backend, RabbitMQ orchestration, Python workers). Emphasizes production-grade reliability (idempotency, retries, strict JSON/schema validation), strong observability with OpenTelemetry, and measurable efficiency gains including ~40% reduction in token usage/cost.”

Sabita Kumari

Screened

Senior Full-Stack AI Engineer specializing in LLM/RAG agentic systems

Boston, MA11y exp

“Built and deployed JobMatcher AI, an LLM-driven workflow automation product for job seekers that extracts requirements from job descriptions, matches to user skills, and generates tailored outreach. Demonstrated strong production engineering by cutting per-run cost ~70%, improving reliability with retries/backoff/fallbacks, and reducing hallucinations via schema validation and templating; also orchestrated the system with LangGraph plus Docker Compose across API, vector DB, and workers.”