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Vetted Software Engineers in Kansas
Pre-screened and vetted in Kansas.
Naveen Sai Alapati
Mid-level Full-Stack Software Engineer specializing in microservices and event-driven systems
Nikhil Ravula
Mid-level Forward Deployed Software Engineer specializing in enterprise SaaS and AI deployments
Logan Holmes
Senior Full-Stack Software Engineer specializing in cloud-native platforms and regulated industries
Karthik O
Mid-level AI Software Engineer specializing in LLM systems and cloud APIs
“Built and productionized an LLM-powered support/knowledge pipeline using embeddings and retrieval (RAG) to deliver more grounded, higher-quality responses while reducing manual effort. Focused on real-world reliability and performance—adding structured validation/guardrails, optimizing vector search and context size for latency/scale, and monitoring failure patterns in production. Experienced with orchestration via LangChain for LLM workflows and Airflow for production data/ML pipelines, and iterates closely with operations stakeholders through demos and feedback.”
Hari teja Nalluri
Mid-Level Software Developer specializing in APIs, backend systems, and CI/CD automation
Sai Bhargav Mannepalli
Mid-level Full-Stack Engineer specializing in healthcare and insurance platforms
Vivekananda Kurri
Mid-Level Full-Stack Developer specializing in cloud microservices and FinTech payments
Supreet P
Mid-Level Full-Stack Software Engineer specializing in cloud-native FinTech systems
“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”
Dimple Galla
Mid-level Data Scientist / AI-ML Engineer specializing in RAG, MLOps, and real-time analytics
“Software/ML engineer who built a production automated job-finding and cold-email personalization system for Fortune 500 outreach, using JobSpy for dynamic scraping, LangChain orchestration, and LLM+vector DB semantic search with grounding/relevance metrics and guardrails. Also delivered a predictive investment analytics platform for financial advisors, communicating results via Tableau dashboards and portfolio KPIs like Sharpe ratio and drawdowns.”
Dinesh Battula
Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems
“Senior full-stack engineer with strong healthcare domain experience who has shipped an Azure OpenAI RAG-based patient medication support chatbot to production, driving ~10K queries/month and a reported 38% reduction in call center volume. Also builds polished real-time React/TypeScript pharmacy tooling and operates large-scale Python/Spark ETL pipelines (~12M records/day) with strong API design, observability, and cloud deployment experience across Azure/Kubernetes and AWS.”
Jonathan Kershaw
Principal AI Platform Architect specializing in enterprise AI operations and governance
Karthik Saripalli
Mid-level .NET Developer specializing in REST APIs, SQL performance, and cloud CI/CD
Satya Sanjna Reddy Paluri
Mid-Level Software Engineer specializing in cloud-native microservices and data platforms
Sathish Chowdam
Mid-level Full-Stack Java Developer specializing in cloud-native microservices and GenAI
Ravi Bheemineni
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Jyothi Pasupula
Mid-level Software Engineer specializing in AI and cloud-native data platforms
Varsha P
Mid-Level Software Engineer specializing in backend APIs, cloud microservices, and LLM integration
Anupriya Palanisamy
Mid-Level Software Engineer specializing in Java microservices and event-driven systems
“Backend-focused engineer with experience spanning research and healthcare: owned a Python/SQL data pipeline that transformed vulnerability-fix code data from SQLite into model-ready JSON for LLM analysis. Also deployed Dockerized Spring Boot microservices to Kubernetes with Jenkins CI/CD and built Kafka-based real-time event streaming (appointment/report events) with idempotent consumers to avoid duplicate processing.”