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Vetted Spring Boot Professionals
Pre-screened and vetted.
Shashank Venkataramana
Mid-level Software Engineer specializing in AWS cloud infrastructure and data platforms
“Backend/infra-focused software engineer who built an autonomous Python API-orchestration agent using asyncio with strong reliability and observability (trace IDs, structured logs, retries/timeouts) and containerized dev workflow. Experienced deploying Python services to Kubernetes with Helm and running GitOps CI/CD via ArgoCD, plus leading an AWS IAM-to-Identity Center migration using CloudTrail-driven least-privilege role design. Also built and debugged a Kafka/SnapLogic bidirectional pipeline syncing Redshift and HBase, resolving missing-record issues via Kibana-driven investigation.”
Smriti Rai
Mid-Level Software Engineer specializing in backend APIs and distributed systems
“JavaScript engineer with Walmart experience contributing to the Yup validation library—reproduced a nested-object validation bug, fixed merge logic, and added test coverage. Strong in systematic debugging/performance isolation (DevTools + timing logs), plus end-to-end ownership including documentation, monitoring, and issue triage.”
Bandla Sai Giridhar
Mid-level Software Engineer specializing in full-stack and cloud-native microservices
“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).”
sarah robert
Staff RPA & Automation Engineer specializing in Financial Services
“Blue Prism RPA developer in a small FinTech-aligned team who owned ~20 production bots and drove both delivery and reliability. Built a shared VDI/locking design that cut infrastructure cost ~20–30% and routinely handled ServiceNow-driven production incidents end-to-end, including hotfixes and longer-term SDLC fixes. Also acted as a player-coach, training junior hires and maintaining high bot success rates (up to 99% within SLA).”
Krishna Madani
Mid-Level Full-Stack Software Developer specializing in cloud-native web applications
“Capgemini engineer with hands-on ownership of production TypeScript backend integrations and loyalty-platform modernization. Built AWS event-driven microservices (SNS/SQS/Lambda) with GraphQL vendor calls and DynamoDB persistence, emphasizing reliability patterns like retries and idempotency; reports ~25% response-time improvement after migrating/optimizing services and workflows.”
Rushwant K
Mid-Level Full-Stack Software Engineer specializing in FinTech and microservices
“Backend engineer with experience at Discover, Dell, and Carpus building high-concurrency microservices and secure APIs. Delivered measurable impact in fintech workflows by integrating credit bureaus (TransUnion/Experian), cutting loan processing from days to minutes and reducing latency 65% through PostgreSQL tuning and caching. Strong in production security patterns (JWT/RBAC, Postgres row-level security for multi-tenant isolation) and low-risk migrations (shadow mode + incremental rollout).”
Sharanya Teegala
Mid-level Full-Stack Software Engineer specializing in Java/Spring and AWS microservices
“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.”
Haritha Jampani
Mid-level Full-Stack Software Engineer specializing in AI and data applications
“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%.”
Upal Kundu
Junior Security Engineer specializing in cloud security and DevSecOps
“Candidate has hands-on experience building and debugging cloud-based backend workflows across AWS and GCP, including a remote desktop deployment for HP, email-to-Google-Sheets automation, and AI/voice backend testing. They stand out for practical infrastructure troubleshooting, API integration work, and lightweight LLM application development with attention to latency, cost, and operational stability.”
William Goff
Principal Software Engineer specializing in MongoDB and Java platforms
“Government and defense software architect with a track record of building mission-critical systems from prototype to long-lived production. Most notably designed Banyan at Fort Meade, a federated SOA platform that achieved 99.9999 uptime and handled 3.2 million daily queries, and later built SBOM automation at Lockheed Martin that was contributed back to the CycloneDX open source ecosystem.”
Ravi Sankar Karuturi
Staff Software Engineer specializing in AI-powered e-commerce search
“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.”
Abhishek Arugonda
Mid-level Backend Software Engineer specializing in cloud-native microservices
“Backend/platform engineer with experience across Cigna, Cognizant, and a university environment, focused on reliability, distributed systems, and regulated-domain workflows. Stands out for combining Kubernetes/Kafka/AWS infrastructure expertise with a production RAG-based healthcare compliance assistant that cut manual reporting work from 30-45 minutes to under 2 minutes while maintaining strong uptime and data-quality controls.”
“Engineer with a thoughtful, hands-on approach to AI-assisted software development, treating AI as a force multiplier for debugging, prototyping, and large-codebase work rather than a substitute for judgment. Particularly strong in multi-agent coding workflows, contract-driven development, and maintaining consistency across backend, frontend, and testing through shared schemas and OpenAPI-based coordination.”
Aniket Dhanawade
Mid-level Full-Stack Engineer specializing in cloud-native and AI-powered applications
“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.”
Phani Konni
Mid-level Full-Stack Software Engineer specializing in agentic AI and document automation
“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.”
Ankit Yadav
Mid-level Software Engineer specializing in cloud-native microservices
“Backend engineer who shipped a Spring Boot transactions/points feature while using AI selectively for boilerplate and test ideas, keeping core system design decisions in human hands. Stands out for rigorous validation of AI output against database behavior, concurrency, idempotency, and failure scenarios, and has also built a lightweight planner -> code gen -> validator agent-style pipeline with step-level logging and retries.”
Abdur Rahman Shaik
Mid-level Front-End Software Engineer specializing in browser-based enterprise UI
“Frontend engineer with strong ownership of complex internal tooling at Phenom, including a high-volume logging and event-trails dashboard used to debug production issues across enterprise clients like MERCK and Regions Bank. Brings a rare mix of UI architecture, browser-performance depth, and product-minded polish, with measurable impact in micro-frontend optimization, developer productivity, and enterprise adoption.”
Rutujeet Falmare
Mid-level Software Engineer specializing in backend microservices and AI-integrated platforms
“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.”
Trisha Shah
Mid-level Software Engineer specializing in AI, cloud, and full-stack systems
“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.”
Sulaxmi Raskar
Senior Full-Stack Software Engineer specializing in AI agents and data platforms
“Full-stack and AI-focused builder who has shipped both customer-facing personalization at AT&T and internal LLM-powered automation/agent systems in startup environments. Stands out for combining TypeScript-heavy engineering rigor with practical AI orchestration, evaluation, and measurable business impact—from reducing support escalation through personalization to saving 10-11 hours per week by automating fragmented operational workflows.”
Sai Naveen Reddy Reganti
Mid-level Full-Stack Engineer specializing in cloud-native FinTech and Healthcare systems
“Full-stack engineer working on customer-facing utility and banking platforms, with hands-on experience across React/React Native, Java/Spring Boot, Python/Django, AWS, and SQL performance tuning. Stands out for owning production systems end to end, improving CI/CD and deployment reliability, and delivering a measurable database optimization that cut CPU utilization from about 80% to 40%.”
Bibek Poudel
Mid-level Full-Stack Developer specializing in FinTech and E-commerce
“Full-stack engineer with experience spanning enterprise AI and e-commerce, including building an agentic orchestration platform and owning a RAG system pipeline at JP Morgan Chase. Stands out for combining React/Node backend delivery with LLM security work, RBAC-heavy system design, and practical SQL/query optimization in production.”
Shivam Soni
Mid-Level Full-Stack Software Developer specializing in cloud-native microservices and AI/ML
“Backend engineer who optimized an AI-driven portfolio analytics/insights platform at Fidelity, addressing latency and traffic growth by moving services toward microservices, improving service communication, and tuning API/DB performance. Experienced scaling Python/FastAPI services with Docker + Kubernetes autoscaling, and strengthening security/privacy for sensitive client portfolio data used in LLM-based reporting.”