Vetted Indexing Professionals

“Early-career engineer who built and launched a zero-to-one AI-driven approval workflow at SDSU that is used daily by roughly 2,000 university users. They owned the system end-to-end—from FastAPI/PostgreSQL backend to React UI—and showed strong judgment around LLM reliability, using a two-step pipeline, validation checks, and human-review fallbacks to cut manual processing time by about 80%.”

“Backend/platform engineer in healthcare and consulting (Molina Healthcare, TCS) who productionized real-time eligibility/authorization and care navigation workflows with strong reliability and HIPAA security. Demonstrated measurable performance gains (≈40% latency reduction, ~99% uptime) using Spring Boot APIs, SQS decoupling, Redis caching, and deep observability, and regularly leads technical demos that accelerate client adoption.”

“Backend engineer with experience in fraud reporting and billing systems, building Java/Spring Boot services behind a React frontend and improving performance 40%+ with caching and SQL optimization while maintaining 99.9% uptime. Has hands-on experience migrating a monolith to microservices with incremental rollout, clear data ownership boundaries, and production-grade API reliability/security practices (JWT/OAuth, RBAC, row-level scoping).”

“Backend-focused Python engineer who has owned production FastAPI services deployed on Kubernetes, including CI/CD (GitLab CI to ECR) and GitOps delivery via ArgoCD/Helm. Has hands-on experience with complex reliability and infrastructure work—solving data inconsistency with validation/partial-data paths, fixing K8s liveness issues via lazy loading, and supporting a phased cloud-to-on-prem migration with dual-writes and monitoring. Also built Kafka-based real-time ingestion consumers handling bursty, high-throughput traffic with async processing and topic/retention tuning.”

“Software engineer (Yellow.ai) who built and productionized an AI-driven resume tailoring system using embeddings + Chroma RAG + QLoRA fine-tuning, deployed via Docker/Kubernetes with CI/CD on a CPU-only Oracle VM. Demonstrates strong reliability/evaluation rigor (custom hallucination/coverage/relevance metrics) and measurable business impact, including a 60% user satisfaction lift from improving chatbot intent accuracy with product and support teams.”

“Customer-facing software engineer who rapidly turns business requirements into Figma prototypes and PoC applications, using workflow prioritization and frequent client reviews to stay aligned. Has hands-on experience integrating with existing authentication/user APIs, building MongoDB-backed caching, and implementing robust fallback/retry mechanisms. Comfortable working on-site with customers and resolving production issues in AWS (e.g., DNS/EC2 traffic routing) in collaboration with DevOps.”

Teja Babu Mandaloju

Screened

Mid-level Data Scientist/MLOps Engineer specializing in NLP, GenAI, and cloud ML platforms

Chicago, USA5y exp

“AI/ML engineer who led production deployment of a multimodal (text/video/image) RAG system on GCP using Gemini 2.5 + Vertex AI Vector Search, scaling to 10M+ documents with sub-second latency and +40% retrieval accuracy. Strong MLOps/orchestration background (Kubernetes, CI/CD, Airflow, MLflow) with proven impact on reliability (75% fewer incidents) and deployment speed (92% faster), plus experience delivering explainable ML (XGBoost + SHAP + Tableau) to non-technical retail stakeholders.”

Harshini Jonnala

Screened

Senior Backend Software Engineer specializing in distributed systems and cloud microservices

Hyderabad, India2y exp

“Backend engineer with NTT Data experience building Java/Spring Boot services for product-data ingestion, including Kafka-based asynchronous pipelines and Redis read-through caching. Also built a personal RAG system deployed on Google Kubernetes Service using FastAPI, LangChain, and Pinecone with multi-tenant data isolation; holds a Master’s background in Machine Learning.”

Sai Erramada

Screened

Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems

Wisconsin, USA6y exp

“Backend engineer with hands-on experience building real-time, event-driven systems at Walgreens, including a Kafka-based prescription status notification service and scalable pipelines for messy prescription/inventory data. Strong focus on reliability patterns (retries, idempotency, DLQs) and iterating based on pharmacist feedback to improve usability.”

Rajeshwar Peri

Screened

Mid-level Data Analyst specializing in healthcare and financial analytics

Chicago, IL5y exp

“Healthcare analytics candidate with hands-on experience turning messy claims and CRM data into validated reporting tables, automating monthly reporting in Python/Airflow, and operationalizing churn metrics in SQL and Tableau. They appear especially strong in stakeholder-aligned metric design and delivered a reported ~10% churn reduction through cohort analysis, segmentation, and at-risk member targeting.”

“Full-stack AI engineer who has owned production deployments for both a voice journaling/emotional insights app and a RAG-based research assistant. Stands out for turning messy, failure-prone LLM and document pipelines into reliable user-facing systems through strong debugging, staged workflow design, and post-launch stabilization.”

“Engineer with hands-on experience embedding AI into software delivery workflows, including Claude-powered PR review, testing, debugging, and multi-agent coding pipelines. They pair AI automation with strong systems thinking around microservices, fault tolerance, multi-AZ design, caching, and security controls like WAF and rate limiting, and also experiment independently with RAG and multi-agent search projects.”

“Built and operated an end-to-end customer-facing "Record Platform" web product as both engineer and primary user, focusing on reliability and correctness in core flows like search and checkout. Implemented a TypeScript/React frontend with a multi-service backend and Kafka-based event-driven architecture, and created internal tooling to automate risky ops like Kubernetes TLS certificate rotation with k6 load/chaos testing (including HTTP/2 and HTTP/3 validation).”

“Full-stack engineer (Devsinc) who built a seed-stage fintech product (Deaglo) for global investment firms, shipping a real-time FX exposure and hedging dashboard using Next.js App Router + TypeScript with Python/C# microservices. Drove major reliability and performance wins by migrating to an async RabbitMQ architecture (DLQs, idempotency) and optimizing Postgres queries (45% faster), while owning monitoring and post-launch backlog.”