Vetted HIPAA Professionals

Deandra House

Screened

Director-level Talent Acquisition leader specializing in global recruiting operations

Plano, Texas19y exp

“Talent/Recruiting Operations leader who has managed 6–20 person TA Ops teams and led a global "Recruiting 2.0" transformation standardizing intake and structured interviews, automating screening/scheduling, and building Power BI funnel dashboards. Delivered measurable impact including ~30% time-to-fill reduction and improved candidate/hiring manager experience, and has hands-on systems implementation experience across Workday Recruiting, SuccessFactors, Eightfold, DocuSign, and background check integrations.”

Sai Swetha Bodlapati

Screened

Senior Data Engineer specializing in Spark, Kafka, and Databricks Lakehouse platforms

Dallas, TX5y exp

“Data engineer at Fidelity who built and operated a real-time financial transactions lakehouse on AWS/Databricks, processing millions of records daily with Kafka streaming. Demonstrated strong reliability and data quality practices (watermarking, idempotent Delta writes, validation/reconciliation, observability) and delivered measurable improvements (~30% faster jobs and ~30% fewer data issues) while enabling trusted gold-layer analytics for downstream teams.”

Sharanya Teegala

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring and AWS microservices

Minneapolis, MN5y exp

“Full-stack engineer with experience at Wells Fargo and Salesforce building regulated, customer-facing financial systems and internal DevOps tooling. Deep in microservices and event-driven architectures (Spring Boot, Kafka/RabbitMQ) with strong CI/CD automation, contract testing, and observability; delivered measurable impact including 60% faster deployments and 40% fewer support tickets.”

“Healthcare analytics professional with TCS/Humana experience turning messy claims and eligibility data into reliable reporting assets using SQL and Python. They combine strong data engineering and analytics execution with stakeholder management, including automating monthly claims reporting from half a day to under 5 minutes and driving a provider outreach effort that reduced claim rejection rates by about 20%.”

Gary Zimble

Screened

Executive COO specializing in healthcare operations, IT, and multi-site transformation

San Diego, CA32y exp

“Candidate indicated they have an active business plan and are working with an investor to raise capital, suggesting entrepreneurial experience and exposure to fundraising. The interview ended early after the candidate declined to discuss current startup details.”

“Built end-to-end ML and GenAI systems at Northern Trust, including a production RAG-based document intelligence platform for financial reports and contracts. Stands out for combining strong MLOps execution with practical product judgment—improving forecast accuracy by 22%, document review accuracy by 38%, and cutting deployment time by 45% while keeping latency and reliability production-ready.”

Niranjaan Munuswamy

Screened

Mid-level Full-Stack Software Engineer specializing in cloud and data engineering

Chicago, IL4y exp

“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.”

“Full-stack engineer with experience spanning AI-powered product features and healthcare fraud detection systems. Has built end-to-end LLM-enabled applications, customer-facing recommendation systems at scale, and operational platforms that improved real-time investigations and flagged over 1,200 high-risk cases quarterly.”

“Backend/data engineer focused on production-grade Python microservices and AWS platforms, including a hybrid Lambda + ECS Fargate architecture managed with Terraform and CI/CD. Has hands-on reliability experience (JWT/OAuth, timeouts, retries, centralized error classification) and built AWS Glue/PySpark ETL pipelines consolidating PostgreSQL/RDS, MongoDB, and S3 sources into curated partitioned Parquet datasets. Demonstrated measurable SQL tuning impact (8 minutes to 25 seconds) and disciplined legacy-to-modern migrations with parity validation and UAT sign-off.”

“Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.”

“ML/AI engineer with healthcare payer experience (Signal Healthcare, Cigna) who has shipped production fraud/claims prediction systems using Python/TensorFlow and exposed them via FastAPI/Flask microservices integrated with EHR and Salesforce. Emphasizes operational reliability and trust—Airflow-orchestrated pipelines with data quality gates plus SHAP-based interpretability, A/B testing, and drift/debug workflows—backed by reported outcomes of 22% lower false payouts and 17% higher model accuracy.”

“Data/ML practitioner with experience at UnitedHealth Group building a fraud claims detection solution combining structured claims data and unstructured notes, validated with compliance stakeholders to improve actionable accuracy. Also applied embeddings, vector databases, and fine-tuned language models in a Bank of America capstone to detect threats/anomalies in financial documents, with production-minded Python ETL workflows using Airflow.”

“Infrastructure/operations engineer with hands-on production IBM Power/AIX (AIX 7.x, VIOS, HMC) and PowerHA/HACMP clustering experience, including DLPAR changes, failover testing, and incident recovery. Also delivers modern cloud DevOps work—GitHub Actions CI/CD for Docker-to-Kubernetes on AWS and Terraform-based provisioning of core AWS infrastructure (VPC/EKS/RDS/IAM) with controlled rollouts and drift checks.”

“Infrastructure/DevOps engineer with strong production ownership across AWS and Kubernetes, including leading real outage recoveries and building governance-heavy IaC/CI/CD in regulated environments. Has designed DR failover testing programs and implemented policy-as-code and peer-reviewed deployment gates to prevent repeat incidents; experience cited at Rackspace, Strategic Systems, and CTS.”

“Full-stack engineer with ~3.5 years of Java Spring Boot and React experience who built an end-to-end banking transaction platform using microservices, Kafka streaming, AWS RDS, and Dockerized CI/CD. Demonstrates strong performance and reliability engineering (async processing, DLQ/retries, idempotency, caching) plus secure cloud deployment practices; has also worked across banking, healthcare, and insurance domains.”

Sai Rahul Dasari

Screened

Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems

USA3y exp

“Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.”

Surya Vamshi Sriperambudooru

Screened

Mid-level AI Engineer specializing in healthcare claims analytics and RAG copilots

Remote, US4y exp

“Built a production "appeals co-pilot" for a healthcare claims appeals team, combining an XGBoost/logistic ranking model with a Python/LangChain RAG stack (FAISS + Mistral 7B) to surface high-probability appeal wins and speed policy-grounded drafting. Emphasizes reliability and trust: hybrid retrieval with metadata routing, citation/eval scripts, guardrails, and an explainability layer that non-technical stakeholders could understand and override.”

“Backend engineer who built an AI-driven "Smart Feedback Analyzer" API (Flask → FastAPI) that processes user feedback with NLP (Hugging Face + OpenAI) and returns structured insights. Demonstrates strong production-minded architecture: stateless services, Cloud Run + Docker deployment, Redis/Celery background processing, and Postgres/SQLAlchemy performance tuning (EXPLAIN ANALYZE, indexing, N+1 fixes), plus multi-tenant data isolation via JWT/API-key derived tenant IDs.”

Mahesh Kota

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native FinTech and Healthcare platforms

New York, NY5y exp

“Backend engineer with production experience building and scaling a Java/Spring Boot payment processing API on AWS (PostgreSQL/Redis) handling a few thousand RPS, including deep performance debugging (connection exhaustion) and observability (CloudWatch, Actuator, Zipkin). Also shipped application-layer AI features (OpenAI email summarizer with feedback loop, ~40% faster agent response times) and designed reliable multi-step workflow orchestration with retries and manual escalation, plus strong SQL tuning and Python engineering practices.”

“Platform/infra engineer with deep Kubernetes (EKS) and VMware vSphere experience who has led a monolith-to-microservices transition for a credit lending decision platform. Built GitOps-driven Terraform delivery with strong governance, and used LaunchDarkly-based progressive rollouts plus Datadog observability to safely ship multiple times per day (reported ~6x throughput and 1/3 the bugfix tickets vs legacy). Also operates hybrid on-prem/AWS networking (firewall + Transit Gateway, BGP) and has handled high-stakes datacenter migrations (100TB Storage vMotion) under Sev1 conditions.”

Shashank R

Screened

Senior Data Engineer specializing in cloud data platforms and real-time analytics

Las Vegas, NV6y exp

“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”

“Full-stack engineer with hands-on experience building real-time operational products across banking, insurance, and startup e-commerce environments. They’ve owned features end-to-end—from React/TypeScript dashboards and Redux performance tuning to Spring Boot, Kafka, AWS Lambda, and production monitoring—and have also shipped 0→1 capabilities where business impact was immediate, such as reducing overselling through inventory visibility.”

Amit Verma

Screened

Mid-level Java Full-Stack Engineer specializing in healthcare and enterprise microservices

Birmingham, AL6y exp

“Developer who actively integrates AI tools like Copilot, ChatGPT, and Cursor into day-to-day coding, testing, debugging, and framework learning to improve delivery speed. They also organize multi-agent workflows across code generation, review, testing, and documentation while retaining final ownership of quality and architecture decisions.”

“Former founder with a successful exit who has since built multiple zero-to-one enterprise platforms across IoT, NLP, and healthcare AI, each cited as generating $1B+ in revenue. Also a Stanford and Alchemist Accelerator mentor, known for using ethnographic research to find product-market fit and for selling multi-million-dollar MVP business cases to C-level executives.”