Vetted SDLC Professionals

“Software engineer with BitSight experience owning and revitalizing a critical internal Entity Management Portal (Django/React), clearing 30+ backlog items and boosting internal workflow efficiency ~40% through performance re-architecture (Redis caching) and disciplined testing. Also built a collaborative chore management platform (React/FastAPI) emphasizing responsiveness (optimistic UI) and scalability (connection pooling, Docker), and improved microservices security by centralizing secrets management with AWS Secrets Manager across multi-cloud environments.”

“Backend/ML systems engineer who built a Flask + PostgreSQL internal ticketing platform and demonstrates strong database/ORM performance depth (indexes, partitioning, RLS multi-tenancy). Notably optimized a high-throughput attachment OCR/embedding pipeline with batching, deduplication, and Redis caching, cutting median latency from 45s to 10s and reducing worker cost by 35% while increasing throughput 4x.”

“Full-stack engineer with hands-on experience building real-time applications (Socket.io chat app) and data-heavy systems in banking/loan management. Comfortable across React and backend services (Spring Boot/Node), with a focus on scalable API design, database performance (indexing/pagination/caching), and deployment via CI/CD and cloud infrastructure.”

“QA automation engineer who owned an end-to-end automated regression suite for a PlayStation digital store flow (login through checkout/payment), building a hybrid POM/data-driven framework from scratch with Selenium/TestNG/Cucumber and also using Playwright/TypeScript and Cypress. Integrated the suite into Jenkins CI/CD with nightly runs and reporting, improved coverage (happy + negative paths), and reduced release risk by catching critical issues like session timeout and transaction/payment defects before production.”

“Senior data scientist with ~5 years’ experience building production ML/NLP systems in finance (Wells Fargo) and deep learning for sensor analytics in connected vehicles (Medtronic). Has delivered end-to-end platforms combining time-series forecasting with transformer-based NLP, including automated drift monitoring/retraining (MLflow + Airflow) and standardized Docker/CI/CD deployments; achieved a reported 22% precision improvement after domain fine-tuning.”

“Early engineer at a fast-growing startup who owned an AI-powered portfolio/site generation workflow end-to-end (frontend in Next.js App Router/TypeScript through backend orchestration). Emphasizes server-first security/performance (Server Components/Actions, revalidation), and production hardening with validation, caching, observability, retries/idempotency, and CI/E2E testing.”

“Backend/full-stack engineer from Foxconn Industrial Internet who led development of a production TypeScript/Node.js facility monitoring platform delivering near real-time manufacturing metrics (e.g., downtime and OEE) using MySQL + InfluxDB and a React dashboard. Demonstrates strong production operations mindset with queue-based workers, idempotency/DLQ patterns, structured observability, and automated Docker + GitLab CI/CD deployments.”

“Backend/microservices engineer (Java/Spring Boot, Kafka, Angular microfrontends) with Teradata experience building distributed analytics/query routing platforms and delivering 20–30% latency reductions through event-driven redesign and reliability hardening. Also built and shipped an end-to-end multimodal medical imaging AI feature (LLaVA/Mistral 7B + LoRA) with production guardrails like confidence-based human review, drift monitoring, and audit logs.”

“Backend/AI engineer who built an AI icon-generation SaaS backend (Java/Spring Boot, MongoDB) on AWS, including async job processing with idempotency and S3-based result storage to handle traffic spikes. Also shipped applied AI in finance—an end-to-end fraud detection pipeline with risk scoring—and designed a banking support AI agent with strict guardrails, audit logs, and human-in-the-loop escalation.”

“Full-stack engineer with recent Mutual of Omaha experience building a cloud-native microservices application in Java/Spring Boot with a React/Angular frontend, integrating multiple AWS services (Lambda, S3, DynamoDB, SQS). Has hands-on experience operationalizing AI features via OpenAI/AWS Bedrock and improving reliability/performance through caching, async processing, and CI/CD pipeline optimization.”

“Customer-facing data engineering professional who builds and deploys real-time reporting/dashboard solutions, gathering reporting and compliance requirements through direct stakeholder engagement. Experienced with Google Cloud IAM governance, secure integrations (encryption, audit logging), and fast production troubleshooting of ETL/pipeline failures with follow-on monitoring and automated recovery improvements; motivated by hands-on, travel-oriented customer work.”

“Backend-leaning full-stack engineer with logistics domain experience (DHL) who shipped a real-time shipment status update system using Spring Boot + Kafka and a performance-tuned PostgreSQL tracking schema. Also has AWS production operations experience (ECS/Kubernetes, Jenkins CI/CD, Terraform/Ansible) and has handled peak-load incidents end-to-end by tracing Kafka lag to database bottlenecks and resolving via query/index optimization plus scaling.”

“QA engineer with 11+ years (nearly 12) in IT across financial, healthcare, and telecommunications domains, experienced partnering closely with developers throughout Agile delivery. Strong in building/maintaining living test plans, running smoke/regression on new builds, and driving triage with impact-based prioritization using Jira/TestRail/Confluence; targets $100k+ base with standard benefits.”

“Full-stack engineer with healthcare domain experience (UnitedHealthcare) delivering real-time claims/eligibility dashboards using Spring Boot microservices and React/TypeScript, with strong AWS/Kubernetes DevOps. Demonstrated measurable impact through performance tuning (33% faster retrieval; 45% faster responses during a 60% traffic spike) and HIPAA-aligned security practices. Also built production FastAPI services for high-volume financial transactions with strong testing and observability (95%+ coverage; Prometheus/Grafana).”

“Full-stack .NET engineer with cloud and applied GenAI experience who shipped a real-time policy status tracking module at Lincoln Financial using ASP.NET Core/.NET 8, Kafka, Angular, SQL Server, Redis, and AKS autoscaling. Also delivered a production internal LLM+RAG support assistant at Honeywell with strong security/guardrails (PII masking, RBAC) and a rigorous eval/regression loop built on a 200-question gold set.”

“QA automation engineer with hands-on ownership of Selenium (C#) and Cypress (JavaScript) suites, including CI integration in GitLab with PR smoke gating and nightly regressions with JUnit reports/screenshots. Drove a reported ~60% reduction in manual effort, improved suite maintainability through reuse/merging tests, and proactively shaped requirements/acceptance criteria in sprint planning to prevent defects (including claims calculation and server/log-related issues).”

“Backend engineer with experience at Cigna evolving REST API services backed by PostgreSQL, emphasizing reliability/correctness, scalability, and observability. Has hands-on production experience with FastAPI (contract-first design, Pydantic schemas), performance tuning (indexes, caching), and secure auth patterns (OAuth/JWT, RBAC, row-level security via Supabase), plus low-risk incremental rollouts using feature flags and dual writes.”

“Backend engineer from Emphasis who modernized legacy, tightly coupled workflow systems into observable, event-driven microservices using Kafka. Led a monolith-to-microservices refactor with shadow traffic, feature flags, canary rollout, dual writes, and reconciliation, and strengthened reliability with idempotent consumers, DLQ/replay, and an outbox pattern to prevent DB/event inconsistency. Strong focus on secure multi-tenant APIs (OIDC/JWT, RBAC/ABAC, Supabase-style RLS) and frontend enablement via OpenAPI and typed client generation.”

“Frontend/platform-leaning engineer who owned a shared React component library (design-system style) adopted across multiple SPAs, with strong discipline around SemVer, deprecation strategy, and developer documentation. Also has backend/distributed-systems experience diagnosing and fixing a Kafka microservice race condition and has led prioritization/migration planning in an unstructured monolith-to-microservices environment (Centene).”

“Full-stack engineer with enterprise experience at Metasystems Inc. (and Qualcomm) building high-traffic, security-sensitive systems—owned a secure transaction processing module end-to-end using Java/Spring Boot, Python/Django, and React. Strong AWS production operations (EKS/ECS/Lambda/RDS/DynamoDB) with IaC (Terraform/CloudFormation), observability, and reliability patterns; also delivered resilient ETL/integration pipelines with idempotency/retries/backfills and achieved a 50% deployment-time reduction through CI/CD and modular refactoring.”

“Backend engineer who built a Python/Flask system for high-volume healthcare claims processing, using PostgreSQL as the source of truth and RabbitMQ workers for scalable async processing. Experienced in SQLAlchemy/Postgres performance tuning, multi-tenant data isolation (including Postgres RLS), and integrating/versioning ML model services (scikit-learn/PyTorch/Hugging Face) with controlled rollouts. Drove measurable performance gains by batching background jobs and adding Redis caching (40% less workload; response times cut from ~10s to 2–3s).”

“Built and deployed a production LLM-powered financial risk and compliance platform to reduce manual trade exception handling and speed up insights from regulatory documents. Implemented a LangChain multi-agent workflow with structured/unstructured data integration (Redshift + vector DB) and emphasized hallucination reduction for regulatory safety using Amazon Bedrock. Strong MLOps/orchestration background across Kubernetes, Airflow, Jenkins, and monitoring/testing with MLflow, Evidently AI, and PyTest.”