Vetted Agile Professionals

“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.”

“Backend-focused engineer who owned an end-to-end Python/Flask service at Viasat powering a 1000+ user internal React app, including API design, Postgres performance tuning (~50% faster), Dockerization, and CI/CD. Demonstrated strong problem-solving by building custom EDN parsing logic and has built near real-time AWS SQS/Lambda pipelines with DLQs and autoscaling patterns; currently ramping on Kubernetes/GitOps (ArgoCD).”

“Backend engineer who owned an order management API built with Python/FastAPI and PostgreSQL, integrating payment and shipping providers with strong reliability patterns (idempotency, async workers, retries/backoff, circuit breakers). Experienced deploying services to Kubernetes using a GitOps model with ArgoCD (auto-sync, self-healing, pruning, rollbacks) and building high-volume Kafka streaming pipelines. Has also supported phased cloud-to-on-prem migrations with a focus on security monitoring/SIEM log continuity.”

“Built ReflectlyAI, an AI-powered interview coach, implementing a low-latency Python/Flask backend with modular LLM/Whisper services, retries/fallbacks, caching/batching, and async/background processing. Demonstrates strong PostgreSQL/SQLAlchemy performance tuning (EXPLAIN ANALYZE, composite indexes, selectinload) and multi-tenant isolation patterns (tenant-scoped schemas, tenant_id middleware), reporting ~50% response-time reduction.”

“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.”

“UX designer (3 years) with a UI engineering background who has built an end-to-end accessible STEM learning experience for blind/visually impaired students, including a MathML-to-MathSpeak parsing solution and multimodal feedback (screen reader, braille keyboard, haptics). Also simplified an AI-driven scoring/onboarding workflow at Founderway.ai using progressive disclosure and iterative usability testing tied to measurable improvements.”

“Healthcare AI/ML engineer with Epic experience who built and deployed a HIPAA-compliant GPT-4 RAG clinical assistant over large medical document sets, emphasizing privacy controls and low-latency performance. Also automated end-to-end retraining and deployment of patient risk models using orchestration/CI-CD (Jenkins, SageMaker, MLflow), cutting deployment time from hours to minutes while improving reliability.”

“Software engineer who built and open-sourced reusable React/Node.js modules (chat, auth, caching) from an AI education platform, emphasizing intuitive APIs and strong documentation. At TCS, improved a healthcare scheduling platform by diagnosing SQL/server bottlenecks and redesigning database + caching, cutting appointment load times by ~40% and reducing support complaints.”

“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.”

“ML/MLOps practitioner from Discover Financial who built and deployed a real-time AI fraud detection platform (LSTM + VAE) on AWS SageMaker with Docker/FastAPI and Jenkins-driven CI/CD. Demonstrated measurable impact (30% accuracy lift, 25% fewer false alerts) and deep expertise in class-imbalance mitigation, drift monitoring, and orchestration (Airflow/Kubeflow), plus strong stakeholder adoption via Power BI dashboards for fraud/compliance teams.”

“Software engineer with robotics and ML background (BS Software Engineering w/ Robotics minor; MS CS w/ ML minor) who built autonomy-focused student robotics projects combining RFID + camera sensing, path planning (Dijkstra), and fuzzy logic, and experimented with neural-network approaches. Also brings production-grade software practices from a Dell software analyst role, emphasizing maintainability, documentation, and testing for real-time systems.”

“Full-stack developer with strong cloud/on-prem focus (AWS, VPC networking) who has improved production reliability by bringing manually created IAM/security group resources under Terraform and standardizing environments. Demonstrated end-to-end troubleshooting across app + infrastructure + networking (traffic capture revealed proxy response truncation) and delivered Python-based monitoring/reporting enhancements that improved ops visibility and turnaround.”

“Worked on large financial analytics datasets combining complaint text, transaction logs, and demographics; built end-to-end NLP/ML pipelines (TF-IDF + Random Forest) and data integration in BigQuery with Tableau reporting, citing ~95–98% accuracy. Also implemented entity resolution with fuzzy matching and semantic linking using BERT sentence-transformer embeddings stored in FAISS, including fine-tuning on labeled pairs to improve search/linking relevance.”

“Startup and early-internet product leader with repeated experience building in new companies and executing pivots. Helped transform a web-based calendar business into a CMS + RBAC platform that became best-in-breed for US K-12 organizations within about three years, emphasizing ROI-driven prototyping and market validation to conserve resources.”

“Customer-facing technical professional with experience spanning engineering and product who advises on application security tradeoffs (threat modeling, API/auth risks, SOC2 mapping) and drives pragmatic remediation plans. Hands-on with Kubernetes/CI-CD agent integrations, secrets management, and log-driven troubleshooting; documented and escalated complex customer environment issues and reported a 40% reduction in bug reporting through workflow automation.”

“Backend-leaning full-stack engineer who led a legacy monolith-to-microservices migration (OAuth, Redis, ActiveMQ) while shipping incrementally via CI/CD to avoid user disruption. Strong in search/filter experiences and performance tuning (Solr schema + relevance boosting) with measurable impact (login reduced to ~5s), plus React/TypeScript UI work including configuration-driven filters and shareable URL state.”

“Full-stack engineer with strong ownership in fast-moving environments: designed and shipped a pre-order/campaign inventory system (NestJS + Strapi + Datadog) that freed 34% warehouse space and reduced stock risk to ~5.7%. Also built rapid, high-impact logistics features (Spot Sales) that drove last-mile cost to ~0 in ~40 days, and has hands-on AWS/Terraform/CI-CD experience including deploying a global RAG system with Pinecone, Datadog, and PagerDuty.”

“QA automation engineer with deep experience owning end-to-end Cypress/JavaScript test suites (smoke, regression, and API contract tests) integrated into GitHub CI with merge gating and rich reporting. Demonstrated healthcare enrollment domain expertise by catching a critical eligibility versioning/overwrite defect via API + DB assertions that UI tests missed, then hardening the pipeline with contract tests and idempotency checks.”

“Full-stack engineer with healthcare and fintech experience who has owned production features end-to-end—most notably an AI assistant clinical risk summary tool on AWS (FastAPI/Lambda + React/TypeScript) that cut analyst review time ~40%. Strong in performance tuning for large datasets (S3/Athena), production ops/observability (CloudWatch, CI/CD, env separation), and building reliable ETL/integrations with idempotency and retries.”

“Has worked at a startup within an incubator program and is a certified mentor with a startup mentorship non-profit focused on early-stage/pre-funded companies. Not currently seeking to found a company or take equity-only roles, but open to working at very early-stage companies (pre-launch/pre-revenue/pre-funded).”

“Full-stack engineer in healthcare and enterprise analytics who has shipped event-driven, near-real-time systems (Spring Boot microservices + Kafka + AWS) and large-scale patient/provider portals (50k+ users). Strong in production reliability and performance—measurably reduced claims latency (27%), cut support tickets (25%), and handled real AWS scaling incidents end-to-end. Also built a Python REST control plane for SDN routing integrated with external reinforcement learning agents.”

“Built and monetized an object-identification app end-to-end (FastAPI backend, HTML/JS frontend, SQLite→Postgres, auth, and an iOS wrapper via Capacitor/Xcode with Apple privacy/policy compliance). Also productionized an AI-native geospatial metadata/QA assistant using LLM+RAG plus deterministic Python validation, measuring impact via time-to-first-pass review and rework rate, and has experience modernizing legacy GIS workflows and delivering across USDA/FEMA-style teams with disciplined Jira-based execution.”

“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.”

Indupriya gummadi

Screened

Mid-level Full-Stack Developer specializing in React/Next.js web applications

Detroit, MI5y exp

“Software engineer with airline operations domain experience building real-time dashboards and internal tools for frontline ops and customer support. Strong in TypeScript/React performance optimization and backend/microservices reliability (RabbitMQ, DLQs, autoscaling, correlation IDs/observability), with a track record of shipping incrementally via feature flags and driving organic adoption through pilot-led iteration.”