Vetted Elasticsearch Professionals

John Chance

Screened

Senior Machine Learning Engineer specializing in conversational AI and healthcare ML

Greenwood, LA9y exp

“ML/AI engineer with hands-on ownership of both classical recommender systems and safety-sensitive LLM agent platforms. They combine production MLOps depth with behavioral health domain experience, including clinical safety validation, explainability, and multi-agent orchestration, and cite measurable impact in both business metrics and latency reduction.”

KAVYA UDATHA

Screened

Mid-level Full-Stack Java Developer specializing in retail, banking, and healthcare systems

Fairborn, OH5y exp

“Full-stack engineer with hands-on ownership of a real-time retail inventory and shipment tracking platform, spanning React/Angular dashboards through Spring Boot microservices, PostgreSQL, and Kafka. Stands out for building operationally impactful systems in ambiguous environments and for thinking carefully about scalability, monitoring, and user-friendly workflow automation, even without direct production AI experience.”

“Backend-leaning engineer at Coforge with strong experience in subscription lifecycle and billing platforms, combining PostgreSQL, MongoDB, Azure, Kubernetes, and messaging systems. Stands out for owning production systems end to end and driving an event-driven architecture shift that reduced failures by 30%+ and improved response times by 40%.”

“Engineering/product leader who builds business-aligned technology roadmaps and scales pod-based orgs with strong delivery discipline (OKRs, CI/CD, QA automation). Led a SaaS supply-chain application adopted by Fortune 100 customers, citing ~$4M MRR and ~87% gross profit, and has hands-on experience standardizing LLM + cloud/MLOps architectures with security/compliance guardrails. Also created the PISEK methodology and used it to run distributed innovation sprints (e.g., an AI ETA predictor moved from pilot to production).”

“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 Developer (recently at Cisco Systems) building end-to-end web applications with Angular frontends and Spring Boot microservices backed by MySQL/JPA, including JWT + role-based access. Has hands-on experience with high-volume, real-time data processing/visualization and has solved complex UI state consistency issues using RxJS BehaviorSubjects; also applies layered state patterns in React with Redux Toolkit and uses AI dev tools (Cursor/Claude) strategically.”

“Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.”

“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.”

“IBM engineer who built and deployed a production RAG-based LLM assistant using LangChain/FAISS with a fine-tuned LLaMA model, served via FastAPI microservices on Kubernetes, achieving 99%+ uptime. Demonstrates strong practical expertise in reducing hallucinations (semantic chunking + metadata-driven retrieval) and managing latency, plus mature MLOps practices (Airflow/dbt pipelines, MLflow tracking, monitoring, A/B and shadow deployments) and effective collaboration with non-technical stakeholders.”

“Cloud/DevOps-focused engineer with production experience in Linux, AWS, Kubernetes, and cloud-native architectures. Has built GitHub Actions CI/CD pipelines for containerized Kubernetes deployments and implemented Terraform-based AWS infrastructure with modular design and remote state/locking (S3 + DynamoDB) plus PR/CI-driven change control.”

“Full-stack engineer with experience at Capital One and Prime Softech owning production systems end-to-end: secure authentication (Java/Spring Security + React/Redux) through AWS ECS deployments with Terraform and CI/CD. Strong reliability/observability focus (Prometheus/Grafana/ELK/CloudWatch) with quantified improvements (15% reliability gain, 30% fewer post-release defects). Also led legacy monolith-to-microservices refactors and built real-time Kafka/Spark ingestion pipelines for analytics/fraud detection.”

“Research Assistant at the University of Houston who built and live-deployed a production RAG system for 1000+ research documents, using hybrid retrieval (dense+BM25+RRF) with cross-encoder reranking and RAGAS-based evaluation; reported 66% MRR, 0.85+ faithfulness, and 68% lower LLM inference costs. Also built a deployed LangGraph multi-agent research system (Researcher/Critic/Writer) with tool integrations (Tavily, arXiv) and dual memory (ChromaDB + Neo4j), plus freelance automation work delivering a WhatsApp chatbot and n8n workflows for a wholesale clothing business.”

Ishaan Umesh Mandliya

Screened

Mid-Level Full-Stack Software Engineer specializing in AI/ML and cloud-native systems

Los Angeles, CA3y exp

“At BondiTech, built and deployed customer-facing backend improvements for enterprise dashboards handling 1M+ records, redesigning a .NET/Entity Framework API with server-side pagination/filtering and feature-flagged rollout to cut latency from ~15s to ~2s. Experienced integrating customer systems into existing APIs, including stabilizing a legacy CRM sync by normalizing inconsistent IDs, handling strict rate limits with batching, and adding DLQs plus reconciliation reporting.”

Bhakti Patel

Screened

Senior Full-Stack Software Engineer specializing in .NET, Python, and cloud-native systems

Worcester, MA11y exp

“Full-stack engineer who owned an end-to-end production feature for a Piraeus Bank stock exchange module, spanning React/TypeScript, backend services, and cloud operations with Docker + CI/CD, delivering reported 90% faster API responses and improved uptime. Also built a Smartwound research MVP on AWS, creating a Python image-processing/scoring pipeline to ship despite unclear image-analysis specs.”

Bandla Sai Giridhar

Screened

Mid-level Software Engineer specializing in full-stack and cloud-native microservices

Dallas, TX4y exp

“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).”

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.”

“Analytics-focused candidate with experience building SQL/Python pipelines and dashboards for donor, campaign, and website performance reporting. They have worked with messy multi-source data, standardized metric definitions, and delivered automated reporting that reportedly reduced manual effort by about 80%.”

“ML/AI engineer with strong production ownership across predictive ML and Generative AI systems. They’ve delivered measurable business impact through real-time churn/drop-off prediction, RAG-based document QA, and scalable LLM optimization, with a consistent focus on reliability, safety, latency, and developer productivity.”

“Built production AI systems for Macy's and Bloomingdale's, including an embeddings-based pipeline to clean trending search queries and an end-to-end 'Ask Macy's' multi-agent chat experience. Brings hands-on experience with real-world agent orchestration, tool integration, quality evaluation, and business-facing safeguards in a large-scale e-commerce environment.”

Aniket Dhanawade

Screened

Mid-level Full-Stack Engineer specializing in cloud-native and AI-powered applications

USA3y exp

“Candidate has a thoughtful, hands-on approach to AI-assisted software development, treating AI as a pair programmer while retaining ownership of architecture, tradeoffs, and final code quality. They have practical experience using multi-agent workflows to ship small features end-to-end, including planning, execution, and gap detection under human oversight.”

“Software engineer who recently shipped an authentication and role-based access feature for a web app, using AI selectively for boilerplate, debugging, and test suggestions while retaining ownership of architecture, security, testing, and final review. Stands out for a disciplined, security-first approach to AI-assisted development and a pragmatic preference for lightweight API-driven solutions over unnecessary framework complexity.”

“Full-stack and AI product engineer with strong AWS/Snowflake experience who built an internal feature flag platform and helped migrate a cybersecurity insights product into a multi-agent AI chat interface. They report production scale of 1M+ embeddings and 50k+ monthly queries, with outcomes including an 80% reduction in analyst work and dashboard generation in 7 minutes; the work was also featured by Claude and AWS.”

“Full-stack product engineer with hands-on ownership from UX/design collaboration through React frontend build, FastAPI/Django services, and AWS deployment. Particularly notable for shipping AI-powered customer support experiences using RAG, LangChain, OpenAI, and Pinecone in a banking context, while also showing pragmatic MVP execution on inventory management workflows.”

“Frontend engineer focused on high-stakes browser interfaces for museums, education, and public exhibits, including kiosks, touch tables, and student platforms. Stands out for combining performance engineering, offline-first resilience, strict typing, and state-machine-driven architecture to deliver polished experiences under hardware, network, and reliability constraints.”