Vetted Blue-Green Deployment Professionals

Pre-screened and vetted.

NP

Namruth Potla

Screened

Senior .NET Software Engineer specializing in enterprise web applications

Dallas, TX5y exp
WalmartNorthwest Missouri State University

Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.

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AB

Ananya Bojja

Screened

Mid-level AI/ML Engineer specializing in healthcare analytics and MLOps

USA4y exp
CignaUniversity of New Hampshire

AI/ML engineer at Cigna Healthcare building a production, HIPAA-compliant LLM-powered clinical insights platform that summarizes unstructured medical notes using a fine-tuned transformer + RAG on AWS. Demonstrates strong end-to-end MLOps and cloud optimization (distillation, Spot/Lambda/Auto Scaling) with quantified outcomes (~28% accuracy lift, ~40% less manual review, ~25% lower ops cost) and strong clinician-facing explainability via SHAP and dashboards.

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SR

Senior Cloud/DevOps Engineer specializing in Azure, Kubernetes, and Infrastructure as Code

Virginia, US5y exp
Electrify AmericaGeorge Mason University

Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.

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RT

Mid-level Machine Learning Engineer specializing in NLP, computer vision, and LLMs

New York City, NY3y exp
WayfairStevens Institute of Technology

Wayfair ML/AI engineer who has shipped and operated production LLM systems for both internal analytics and customer-facing assistants. Stands out for combining strong RAG/retrieval engineering with production-grade platform work—improving trust, reducing latency by ~30%, and cutting ad hoc reporting demand by ~50%.

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VT

Mid-level AI/ML Engineer specializing in Generative AI and agentic systems

4y exp
WalmartUniversity of Central Missouri

Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.

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AM

Mid-level Full-Stack Software Engineer specializing in React, Spring Boot, and AWS

Los Angeles, CA5y exp
QualcommCalifornia State University, Northridge

JavaScript/TypeScript engineer with proven open-source impact: delivered a major reliability upgrade to a retry/error-handling library (standardized typed errors, added exponential backoff, expanded Jest tests, and implemented GitHub Actions CI) that was merged and released. Demonstrates strong performance engineering and debugging skills (profiling-driven optimization; diagnosed a race condition causing inconsistent retries) plus a documentation-first approach to developer experience.

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KR

Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps

Texas, USA4y exp
McKessonUniversity of Texas at Arlington

AI/ML engineer with healthcare domain depth who led a HIPAA-compliant, production LLM system at McKesson to automate clinical document understanding—extracting entities, summarizing provider notes, and supporting authorization decisions. Hands-on across Spark/Python ETL, Hugging Face + LoRA/QLoRA fine-tuning, RAG, and cloud-native MLOps (Airflow/Kubernetes/Step Functions, MLflow, blue-green on EKS/GKE), with explicit work on PHI handling and hallucination reduction.

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VM

Senior DevOps & Release Engineer specializing in CI/CD automation and AWS IaC

Raleigh, NC12y exp
VidmobUniversity of Central Missouri

Infrastructure/DevOps engineer (Vidmob) focused on AWS + containers, owning GitLab CI/CD and Terraform-managed environments. Led a high-impact CI incident by correlating runner queue time, Docker pull latency, and NAT egress; implemented ECR pull-through caching and VPC endpoints to restore performance and then standardized the fix in Terraform for future scale-ups.

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KK

Mid-level Data Scientist specializing in MLOps, LLM/RAG applications, and deep learning

United States5y exp
CitigroupUniversity of North Texas

Built and deployed a production compliance automation RAG system (at Citi) that generates citation-backed, schema-validated risk summaries for regulatory document review. Emphasizes regulated-environment reliability with retrieval-only grounding, abstention, confidence thresholds, and immutable audit logging, plus orchestration using LangChain/LangGraph and Airflow. Reported ~60% reduction in compliance review effort while maintaining high precision and traceability.

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CR

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

Phoenix, AZ4y exp
ServiceNowWestern Illinois University

Software engineer with hands-on ownership of both fintech checkout improvements (saved payment methods/one-click checkout with tokenization and feature-flag rollouts) and production LLM/RAG systems for customer support. Demonstrates strong operational rigor via guardrails, evaluation loops integrated into CI/CD, and scalable data pipelines handling messy PDFs/CSVs/logs with reliability and observability.

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Jeetendra Girish Vasisht - Junior Software Engineer specializing in cloud-native microservices in Bangalore, India

Junior Software Engineer specializing in cloud-native microservices

Bangalore, India2y exp
NokiaIllinois Institute of Technology

Backend engineer (Nokia) who designs and migrates cloud-native microservices at scale, including a secure low-latency system handling 500k+ daily transactions. Strong in Kubernetes/OpenShift operations, CI/CD standardization, and production security (OAuth2/JWT/RBAC) with SOC2-aligned controls and zero critical security incidents. Demonstrated expertise in safe migrations (canary/blue-green, dual writes, reconciliation) and concurrency correctness in real-time systems.

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Hetvi Shah - Mid-Level Full-Stack Software Developer specializing in React/Angular and Node.js in Toronto, Ontario

Hetvi Shah

Screened

Mid-Level Full-Stack Software Developer specializing in React/Angular and Node.js

Toronto, Ontario6y exp
TELUSConcordia University

Frontend lead who owned architecture and quality for TELUS’s Next Generation Sales Platform, building a modular React+TypeScript experience that scaled across wireline/wireless products and channels. Experienced in hardening UIs against unreliable backend integrations (API abstraction, retries/fallbacks, caching, logging) and delivering real-time dashboards via WebSockets, with strong CI/CD testing and blue-green release practices for high-stakes launches like Black Friday.

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JH

Principal Software Engineer/Consultant specializing in cloud, geospatial, and enterprise platforms

Minneapolis, MN16y exp
NextEra AnalyticsUniversity of Minnesota

Runs two lean real estate companies remotely by building local on-the-ground contact networks and leveraging free-tier technology to keep total annual business costs under $100. Brings a cost-elimination and MVP/validation-first mindset, preferring to join an established company unless a clearly viable business idea emerges.

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Mukul Sai Pendem - Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps in United States (Remote)

Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps

United States (Remote)4y exp
Saayam for AllNortheastern University

Backend engineer with strong Python/FastAPI microservices ownership, including an ML-serving service with embeddings, async DB access, and Redis caching to reduce latency under high load. Experienced deploying and operating containerized services on Kubernetes using GitOps (Argo CD/Helm) with automated CI/CD, plus hands-on Kafka streaming pipeline tuning and enterprise migration work (Infosys) using blue-green/active-passive strategies.

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Rohit Vibhu Channananjundarya - Mid-level Software Engineer specializing in distributed systems and full-stack platforms in Chicago, IL

Mid-level Software Engineer specializing in distributed systems and full-stack platforms

Chicago, IL6y exp
ExpediaUniversity of Illinois Chicago

Engineer who treats AI as a force multiplier rather than a replacement for judgment, with hands-on experience using tools like Claude Code, Cursor, Copilot, and Codex across planning, coding, testing, and review. Particularly notable for building a multi-agent PR review system that automated summarization, risk scanning, schema validation, and test suggestions, helping the team shift reviewer time toward architecture and business logic.

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GL

Mid-level Software Engineer specializing in Java microservices for FinTech

Texas, USA4y exp
JPMorgan ChaseUniversity of South Florida

Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.

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SS

Sowmya Sree

Screened

Mid-level Machine Learning Engineer specializing in LLM agents, RAG, and MLOps

Dallas, TX5y exp
Bank of AmericaUniversity of North Texas

Built production LLM systems including a real-time customer feedback analysis and workflow automation platform using RAG and multi-agent orchestration with confidence-based human escalation, addressing privacy and legacy integration challenges. Also automated ML operations with Airflow/Kubernetes (e.g., daily churn model retraining) cutting retraining time to under 30 minutes, and demonstrates a rigorous testing/monitoring approach plus strong non-technical stakeholder collaboration.

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Sai Kondapaka - Mid-Level Software Engineer specializing in microservices, data pipelines, and FinTech fraud detection in Remote, USA

Sai Kondapaka

Screened

Mid-Level Software Engineer specializing in microservices, data pipelines, and FinTech fraud detection

Remote, USA5y exp
PayPalCalifornia State University

Backend engineer with PayPal experience owning a high-throughput, low-latency fraud detection pipeline processing billions of transactions/day, integrating LLM-based models into real-time Kafka streams and payment decisioning APIs. Strong Kubernetes + GitOps practitioner (declarative, auditable deployments; autoscaling/probe tuning) with migration experience modernizing legacy systems onto AKS/OpenShift.

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SNEHA KUSUMA - Mid-level Java Full-Stack Developer specializing in banking and telecom platforms in Dallas, TX

SNEHA KUSUMA

Screened

Mid-level Java Full-Stack Developer specializing in banking and telecom platforms

Dallas, TX5y exp
U.S. BankUniversity of Central Missouri

Frontend-focused engineer with experience at T-Mobile and U.S. Bank who maintained a TypeScript utility library (types, tests, build pipeline, and docs) adopted by multiple teams, and improved React workflow performance by refactoring components and optimizing data fetching. Known for pragmatic cross-team support—reproducing issues quickly, shipping well-tested fixes, and managing changes carefully to avoid breaking downstream apps.

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Sreelekha Vuppala - Mid-level Data Scientist specializing in Generative AI, MLOps, and cloud data platforms in USA

Mid-level Data Scientist specializing in Generative AI, MLOps, and cloud data platforms

USA4y exp
CitiusTechArizona State University

GenAI/ML engineer (CitiusTech) who has deployed production RAG systems for compliance/operations document Q&A, using Pinecone + FastAPI microservices on Kubernetes with strong monitoring and guardrails. Also built a GenAI-powered incident triage/routing solution in collaboration with non-technical stakeholders, achieving 35% faster response times and 40% fewer misclassified tickets, and has hands-on orchestration experience with Airflow and AutoSys.

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Deeresh Gajjala - Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems in Dallas, TX

Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems

Dallas, TX6y exp
American ExpressUniversity of Central Missouri

Senior software engineer with Amazon experience who owned end-to-end improvements to a real-time payment authorization service, rebuilding it as a reactive Spring WebFlux microservice with saga orchestration and Kafka event streaming, deployed on AWS EKS with strong observability. Also built React+TypeScript and Node/Express full-stack workflow apps (onboarding, campaign management, admin review) and has experience shipping quickly in ambiguous startup environments while maintaining reliability and data correctness.

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Sanket Mungikar - Mid-level Software Engineer specializing in backend systems and real-time analytics in California, USA

Mid-level Software Engineer specializing in backend systems and real-time analytics

California, USA5y exp
BigCommerceCalifornia State University, Fullerton

Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.

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Supreet Purthpli - Mid-level AI/ML Software Engineer specializing in cloud-native MLOps and FinTech in San Francisco, CA

Mid-level AI/ML Software Engineer specializing in cloud-native MLOps and FinTech

San Francisco, CA4y exp
JPMorgan ChaseUniversity of Kansas

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%.

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