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Vetted Monitoring Professionals

Pre-screened and vetted.

MonitoringPythonDockerCI/CDAWSKubernetes
JK

Justin Kato

Senior Technical Support Engineer specializing in cloud and distributed systems

San Jose, CA11y exp
WilloWeb, Inc.Eastern Washington University
AlertingAnsibleAuthenticationAutomationAWSBash+64
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GP

Gitesh Pawar

Mid-Level Full-Stack Software Engineer specializing in Cloud, Microservices & Distributed Systems

USA6y exp
State StreetCalifornia State University
AjaxAmazon DynamoDBAmazon EC2Amazon EKSAmazon S3Amazon SQS+127
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VR

Vamsi Reddy

Mid-level AI/ML Engineer specializing in cloud MLOps and scalable model deployment

Detroit, MI6y exp
Ally BankIndiana Wesleyan University
PythonJavaSQLBashPowerShellTensorFlow+77
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JM

Jenvith Manduva

Mid-level Machine Learning Engineer specializing in Generative AI and MLOps

USA4y exp
Piper SandlerNortheastern University
PythonSQLPySparkJavaRPyTorch+140
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AS

Aryan Shirwadkar

Mid-level AI/ML Engineer specializing in Generative AI and MLOps

USA4y exp
Northern TrustSyracuse University
PythonRC++JavaJavaScriptTypeScript+98
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AS

Amy Salnikov

Senior Software Engineer specializing in backend systems, AWS cloud services, and data pipelines

Houston, TX13y exp
BroadridgeHebrew University of Jerusalem
PythonFastAPIFlaskTypeScriptJavaScriptREST APIs+43
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BS

Brandon Samudio

Screened

Senior Backend Software Engineer specializing in automation microservices

San Ramon, California6y exp
IntelygenzUC Santa Cruz

“Backend Python engineer who built core services for a telecom automation engine monitoring thousands of routers in real time and auto-generating support tickets. As the sole Intelygenz engineer on the project, they diagnosed a costly Terraform/GitLab CI/CD resource-leak issue in AWS and implemented a cleanup redesign that eliminated orphaned resources and reduced client cloud spend. Also shipped applied-AI ticket triage suggestions via API integration and built an end-to-end Gmail-to-ticket ingestion workflow.”

AgileBackend developmentCC#C++CI/CD+78
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SR

Srinandh Reddy

Screened

Mid-Level Software Engineer specializing in backend, cloud, and event-driven systems

Aurora, Illinois5y exp
McKessonLewis University

“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”

PythonJavaJavaScriptTypeScriptReactAngular+106
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KK

Kajol Khatri

Screened

Senior Software Engineer specializing in backend, DevOps, and LLM-powered systems

San Jose, CA5y exp
CBREUniversity of Texas at Arlington

“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.”

PythonJavaSQLJavaScriptC++TypeScript+116
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LM

LakshmiA Makena

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices

Seattle, WA4y exp
SiemensUniversity of North Texas

“Backend engineer with experience in both healthcare (Siemens) and payments (Bitwise), focused on scaling Python APIs and modernizing architectures. Has led monolith-to-microservices migrations and introduced Kafka async processing, Redis caching, and ELK observability, citing ~40% faster issue resolution and improved reliability via idempotency and strong security controls (OAuth2/JWT, RBAC, RLS).”

PythonJavaC++C#JavaScriptFastAPI+76
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AN

Austin Near

Screened

Mid-Level Software Engineer specializing in full-stack and backend systems

Santa Clara, CA3y exp
Rocket EMSUC Merced

“Full-stack JavaScript developer in small-company environments building PCB manufacturing web tooling. Owned and delivered blob-storage upload/download infrastructure (including an internal developer library) and a training/compliance tracking tool. Implemented secure, broadly compatible SSO for a customer portal under a <1 month deadline tied to an 8-figure customer deal, despite having no prior authentication experience.”

PythonC#C++JavaScriptTypeScriptSQL+81
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UP

Ugender Peddi

Screened

Mid-level Full-Stack Developer specializing in healthcare cloud applications

USA4y exp
HCA HealthcareMissouri University of Science and Technology

“Master’s-program backend engineer with strong Java/Spring Boot industry experience who also owned a Python analytics service (Flask/Postgres, JWT, Celery/Redis) and optimized large-dataset performance via SQL/batching. Has hands-on Kubernetes microservices deployment and GitLab+Terraform CI/CD/GitOps workflows, plus experience supporting phased on-prem to AWS migrations and building Kafka-based real-time streaming pipelines.”

JavaSQLPL/SQLCC++JavaScript+109
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MP

Mohana pavan Vankayala

Screened

Mid-level Java Full-Stack Developer specializing in microservices and AWS

Overland Park, KS4y exp
HCLTechUniversity of Central Missouri

“Full-stack engineer (HCL Tech) with 4 years building enterprise, high-throughput microservices on AWS/Azure using Java/Spring Boot and React. Demonstrated measurable performance gains (40% throughput) through Redis caching, deep SQL/query tuning, and Kafka-based async refactors, plus strong DevOps/observability practices with Jenkins/CloudFormation and Datadog/Splunk.”

JavaJSPSQLPL/SQLSpring BootSpring MVC+95
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JP

Jay Patel

Screened

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

USA6y exp
State StreetPace University

“ML/LLM engineer with production experience building a RAG-based LLM support assistant (FastAPI, Redis, Kafka) with multi-layer validation and human-in-the-loop feedback loops to improve accuracy over time. Has orchestration and MLOps depth using Airflow and Kubeflow on Kubernetes (autoscaling, alerting, monitoring) and delivered measurable ops impact (40% ticket efficiency improvement) by partnering closely with customer support teams.”

PythonRSQLPyTorchTensorFlowscikit-learn+106
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SA

Sadha Alla

Screened

Mid-level Software Engineer specializing in Java microservices and ML model integration

Chicago, IL5y exp
Berkshire HathawayRoosevelt University

“Backend/ML platform engineer who owns end-to-end delivery of ML-serving APIs (FastAPI + TensorFlow) and runs them reliably on Kubernetes using ArgoCD GitOps. Has hands-on experience solving production-only issues (probe tuning for model warm-up, resource profiling) and building scalable Kafka streaming pipelines, plus supporting phased on-prem to AWS migrations with dependency discovery and recreation of hidden jobs/workflows.”

JavaMultithreadingSpring BootSpring FrameworkHibernateSpring Security+133
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BC

Babji Challagiri

Screened

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

Columbus, OH5y exp
SynchronyWright State University

“Software engineer with experience at Synchrony and HCL delivering end-to-end production systems: a secure, Kafka-driven transaction processing microservice with React real-time status tracking, containerized and deployed on AWS Kubernetes via Jenkins with ELK/CloudWatch monitoring. Has hands-on incident ownership and performance tuning (DB/query/index/pooling) driving ~20–30% latency improvements, plus built internal Python monitoring APIs with strong reliability and observability.”

JavaTypeScriptJavaScriptSQLPythonSpring Boot+128
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SV

sasaunk Vanamali

Screened

Mid-level Full-Stack Software Developer specializing in cloud-native microservices

USA4y exp
Cleveland ClinicBowling Green State University

“Built a real-time telemedicine clinician dashboard and iterated post-launch by diagnosing lag via logs/metrics and optimizing DB queries/sync logic. Also shipped a production internal RAG knowledge assistant for support teams, including embeddings/vector DB, citation-only answers with abstention thresholds, and an eval loop driven by real ticket data that improved accuracy through chunking/overlap and batching optimizations.”

AgileAmazon API GatewayAmazon CloudFrontAmazon DynamoDBAmazon EC2Amazon ECS+92
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BA

Bilal Ahmed

Screened

Senior Linux Systems Engineer specializing in hybrid cloud and DevOps automation

7y exp
ASM ResearchCollege of Staten Island, CUNY

“Cloud/infrastructure engineer from ASM Research supporting federal healthcare systems, operating multi-cloud (AWS/Azure/GCP) environments at ~2000-server scale. Deep hands-on experience with Terraform/Ansible IaC, PR-based governance (Atlantis), and secure CI/CD (OIDC/least privilege), with concrete incident response wins and HA/failover testing improvements. Not an IBM Power/AIX specialist but comfortable translating virtualization/partitioning and ops practices to new platforms.”

LinuxAWSAmazon EC2Amazon S3Amazon RDSAmazon EKS+156
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SB

Shreyansh Bhalani

Screened

Mid-level Full-Stack & ML Engineer specializing in AI SaaS, MLOps, and cloud infrastructure

Edison, NJ3y exp
AffirmoAINYU

“Built and shipped an AI-powered driver ranking/assignment system at AffirmoAI using LLM intent classification + RAG over pgvector/Postgres, served via FastAPI with a React UI that explains scores. Drove measurable improvements through optimization and iteration (latency down to <800ms, adoption 60%→90%+) and implemented rigorous eval loops with dispatcher ground truth plus cold-start handling for new drivers.”

PythonJavaScriptTypeScriptSQLJavaC+++120
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AA

Archi Agrawal

Screened

Mid-level Software Developer specializing in microservices and AWS cloud-native systems

United States3y exp
Saayam for AllArizona State University

“Full-stack engineer focused on application-layer product work (70–75%), with production experience building real-time operational dashboards (React/TypeScript + Node/Express + WebSockets + Postgres) and measurable impact (50% reduction in data entry time). Also owned a Flask backend for a SaaS product with token auth/RBAC, versioning, observability, and performance tuning, and has operated containerized apps on AWS (EKS, RDS/Aurora, S3, API Gateway) including handling a real latency/scaling incident end-to-end.”

AgileAPI GatewayAuthenticationAuthorizationAWSAWS Lambda+91
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SE

Sai Erramada

Screened

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

Wisconsin, USA6y exp
WalgreensConcordia University Wisconsin

“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.”

JavaSQLJavaScriptSpring BootSpring FrameworkSpring MVC+102
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SK

Srichandan Kota

Screened

Senior Full-Stack AI Engineer specializing in Generative AI and FinTech

Minneapolis, MN6y exp
QuantLink AIUniversity of North Texas

“Backend engineer who built and owned an AI-powered financial research product end-to-end, using a typed NestJS/GraphQL backend with LangGraph-style agent routing to produce sourced, structured financial analysis. Emphasizes finance-grade correctness (Zod validation, metric registries, unit/empty-result guardrails) while keeping latency low via batching, caching, and fast token streaming, and has led incremental migrations using strangler/feature-flag/shadow traffic patterns.”

AgileAmazon BedrockAmazon DynamoDBAmazon EC2Amazon EKSAmazon RDS+136
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AB

Anas Baig

Screened

Junior Software Engineer specializing in full-stack web and cloud systems

Boston, MA2y exp
EnFi, IncNortheastern University

“Co-op engineer at EnFi who built and maintained a multi-tenant prompt library and LLM workflow tooling used by internal teams and external enterprise clients. Led TypeScript/React package design and standardized a typed workflow abstraction across disparate implementations (React, Go, JSON), improving reliability and developer adoption. Delivered measurable performance gains (~25% latency reduction) and owned end-to-end execution including docs, demos, debugging, and deployment.”

GoPythonTypeScriptJavaScriptSQLJava+125
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