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I'm a 7+ years experienced Senior Full Stack Developer with a strong focus on backend systems and end-to-end architecture. Most of the work I take on involves systems that are already running in production; often with messy code, inconsistent logic, or performance issues. I’m used to stepping into those environments, understanding how things actually work (not just how they were intended), and then restructuring them into something more stable, maintainable, and easier to extend. From an architectural perspective, I work across the full stack — but my strength is in designing backend systems that handle real-world conditions: concurrent traffic, partial failures, and evolving requirements. I’ve worked extensively with microservices-based designs, async processing, and cloud-native setups, where clear service boundaries and predictable data flow matter more than just writing endpoints. More recently, I’ve been integrating AI into backend workflows — building systems that incorporate LLMs, transcription pipelines, and automated data processing. The challenge there isn’t just integration, but making sure these systems behave reliably under production constraints (latency, retries, streaming responses, and cost control). On the frontend side, I’m comfortable building and adjusting interfaces using React or similar frameworks, mainly to ensure the backend and UI work together cleanly and efficiently. If you have an existing system that needs to be cleaned up, scaled, or extended — especially with AI or cloud-based architecture — I can step in and take ownership of both the technical direction and implementation. 🔹 What I Work On ✅Restructuring and stabilizing existing production systems ✅Designing and implementing backend architectures (monolith → microservices) ✅Building and optimizing APIs (Python, Node.js) ✅AI integration (LLMs, transcription, automation pipelines) ✅Async processing (queues, workers, streaming systems) ✅Cloud-based systems (AWS, GCP, containerized deployments) ✅Frontend integration (React, API-driven UI) ✅Performance tuning and reliability improvements 🔹 Example Work 👉 Production System Refactor & Stabilization Stepped into an existing backend with tightly coupled logic and inconsistent behavior. Broke down responsibilities, clarified data flow, and restructured services to improve reliability and maintainability without disrupting live usage. 👉 Microservices & Cloud Migration Helped transition a monolithic backend into a service-based architecture. Defined service boundaries, introduced async communication patterns, and deployed using containerized infrastructure. 👉 AI-Integrated Backend System Built a backend pipeline combining real-time transcription and LLM-based processing. Addressed latency issues through buffering, retry strategies, and controlled request flows to keep the system stable under continuous usage. 👉 Full Stack Feature Delivery Implemented end-to-end features including backend APIs, database design, and frontend integration. Ensured consistency between data models, API contracts, and UI behavior. 💻 Tech Stack Frontend: React.js, Next.js, Vue.js, Tailwnd CSS Backend: FastAPI, Django, Flask, Node.js (Express/Nest.js), Supabase, Firebase AI & Automation: OpenAI API, Claude, LLM-based pipelines, Custom chatbots, task automation Architecture: Microservices, REST APIs, event-driven systems Cloud & DevOps: AWS, GCP, Docker, Kubernetes Databases: PostgreSQL, MongoDB, Redis Need solid system? – Let’s work together 🚀

Project Experience Apple - Site Reliability Engineer working with AWS and internet systems at Apple Sapiens - Senior AWS & Azure Cloud & DevOps Engineer Modus Create - Senior AWS DevOps Engineer & SRE - AWS CloudWatch Synthetics implementation and SRE best practices implementation Surge Forward - AWS Migrations Specialist - completed migration of IBM Netezza to AWS Redshift Hansen Technologies - AWS Cloud Engineer - Completed large scale migration from on premises Data Center to AWS Linux Academy - Cloud Training Architect Cloud Academy - Cloud Training Architect

I'm a Senior Software Engineer specializing in AI engineering, cloud-native systems, backend architecture, and SaaS development, with a strong focus on FinTech and Financial Services. I build production-grade software across the AI, application, data, and infrastructure layers, combining modern AI capabilities with strong software engineering and cloud architecture to create secure, scalable, and maintainable systems. ◆ AI Engineering My primary focus is production AI and LLM application engineering. I build AI systems that connect models with real application data, APIs, databases, internal knowledge, and business workflows. My AI work covers Generative AI, LLMs, OpenAI, Anthropic/Claude, prompt engineering, structured outputs, embeddings, RAG, vector search, reranking, tool/function calling, AI agents, workflow automation, evaluation, observability, latency optimization, reliability, and AI cost optimization. ◆ Backend & Software Architecture I design and build scalable backend systems across modern and enterprise environments, using Python, FastAPI, Node.js, TypeScript, Java, Spring Boot, Django, and Flask. my engineering scope includes API architecture, REST services, authentication, authorization, asynchronous processing, background jobs, messaging, caching, database design, microservices, distributed systems, service integration, fault tolerance, performance optimization, scalability, and system design. ◆ Cloud & Production Engineering I design and deploy production cloud environments primarily on AWS, covering infrastructure, networking, security, compute, containers, orchestration, data services, messaging, automation, and observability.my cloud stack includes AWS, VPC, IAM, EC2, ECS, EKS, Lambda, S3, RDS/Aurora, ElastiCache, SQS, SNS, EventBridge, CloudWatch, Docker, Kubernetes, CI/CD, Infrastructure as Code, monitoring, logging, metrics, alerting, high availability, fault tolerance, disaster recovery, scalability, security, performance, and cost optimization. for AI workloads, I also consider AI service architecture, asynchronous inference, workload scaling, model/API latency, data security, resource utilization, and AI infrastructure cost as part of the overall cloud design. ◆ Data & AI Infrastructure I work with PostgreSQL, Redis, vector databases, vector search, embeddings, document processing, retrieval systems, and knowledge-based architectures. for relationship-heavy data and enterprise knowledge systems, I can incorporate Neo4j and knowledge graph architectures. For deeper machine learning workflows, I understand the role of PyTorch and TensorFlow alongside modern LLM and AI application development. ◆ FinTech, Financial Services & SaaS My primary industry direction is the intersection of AI, FinTech, Financial Services, and SaaS. I'm particularly interested in AI-powered financial platforms, financial workflow automation, intelligent document processing, financial data applications, analytics and decision-support systems, secure financial APIs, enterprise SaaS, business process automation, and AI-powered enterprise applications. Financial software requires strong attention to security, data integrity, access control, auditability, reliability, scalability, and operational stability, which I consider fundamental parts of system architecture. ◆ Core Technology Areas AI: Generative AI · LLMs · RAG · AI Agents · Embeddings · Vector Search · OpenAI · Anthropic/Claude · PyTorch · TensorFlow Software: Python · FastAPI · Node.js · TypeScript · Java · Spring Boot · Django · Flask · REST APIs · Microservices Cloud: AWS · VPC · IAM · EC2 · ECS · EKS · Lambda · S3 · RDS/Aurora · ElastiCache · SQS · SNS · EventBridge · CloudWatch · Docker · Kubernetes · CI/CD Data: PostgreSQL · Redis · Vector Databases · Search · Neo4j · Knowledge Graphs Architecture: Distributed Systems · System Design · Scalability · High Availability · Fault Tolerance · Security · Observability · Performance · Cost Optimization I'm particularly interested in long-term engagements and full-time opportunities where I can take ownership of architecture, AI engineering, backend systems, cloud infrastructure, and production delivery. My focus is building reliable, scalable AI-powered software that solves real business and financial problems and is engineered for production from the beginning.

I build practical web applications and internal tools that help small businesses and growing organizations replace manual work, connect their systems, and serve customers more effectively. I am a web application engineer with a broader background in systems, cloud, automation, APIs, and production operations. That means I can work beyond a local prototype: I can help clarify the workflow, build the application, connect the services it depends on, deploy it, and leave the team with something they can maintain. Projects I can help with include: - Customer portals, internal dashboards, and administrative tools - Intake, approval, scheduling, inventory, and reporting workflows - Replacing spreadsheet-and-email processes with a simple web application - API integrations between business tools and SaaS platforms - Custom forms, authenticated workflows, and role-based access - Small business websites with application features and back-office tools - Data import, cleanup, search, and reporting interfaces - Improving, documenting, and deploying an existing application - Automating repetitive operational tasks with scripts, APIs, and background jobs - Hosting, deployment, backups, monitoring, and reliability improvements My approach is project-oriented: 1. Understand the current workflow and define the smallest useful outcome. 2. Build a focused first version instead of over-engineering a large platform. 3. Deploy it into a maintainable environment with clear handoff documentation. 4. Identify sensible follow-on improvements only after the first result is working. Selected experience includes reducing deployment time from 96 minutes to 13 minutes across 15+ microservices, recovering a production Ceph cluster with zero data loss, building cloud and Kubernetes platforms, integrating enterprise and business systems through APIs, and delivering web and automation work for real organizations. I bring 8+ years across web applications, Linux, cloud infrastructure, CI/CD, databases, automation, security, and operations. I am comfortable taking ownership of a project that crosses the boundary between application code and the systems required to run it. My Upwork track record includes 36 jobs, 1,890 hours, $70K+ in earnings, a 100% Job Success Score, and Top Rated status. If you are considering a project, send me: - What process or application needs to improve? - Who will use it and what do they need to accomplish? - What systems, data, or services must it connect to? - What would make the first version successful? I can help turn that into a focused first project with a clear outcome and scope.

Struggling with legacy systems, data chaos, high Azure costs, or risky migrations? With 15+ years of experience and a 50-engineer team, I deliver proven medallion architecture, optimized data warehouses, seamless migrations, and a single source of truth to cut costs and drive clarity. Advanced T-SQL | DAX | Fabric Medallion | ADF, SSIS, config-driven meta data ETL Pipeline | Python | PySpark | Databricks (DLT, Lakeflow) | AWS Glue | Lambda | SharePoint | DOMO, Tableau to Power BI | Azure AI Foundry | Azure AI Search (RAG) | Azure Functions | Fabric Data Agent About Me I'm a senior Azure Data Architect and Microsoft Fabric expert helping organizations build, optimize, and modernize their cloud data infrastructure. From Fortune 500 companies to agile startups, I design scalable systems that simplify analytics, streamline pipelines, and unlock real business insights. I also build AI-powered agents and copilots that let business users query governed data in plain language, backed by retrieval-augmented generation and deterministic, auditable logic. As Co-Founder of a Microsoft Partner firm and a proud U.S. citizen, I offer enterprise-level expertise without the overhead. You'll work directly with the architect who's led successful projects for Microsoft, CVS, Toyota, LinkedIn, Wells Fargo, Otsuka Pharmaceutical, DHS, United Health Group, Coca-Cola, UBS, Capgemini, and multiple large law firms — no middle layers, just results. Skills & Expertise - Cloud: Azure, AWS - Data Engineering: ADF, SSIS, Databricks, ETL Pipelines - Analytics & BI: Power BI, DAX, Tableau, DOMO, SQL - Data Warehousing: Azure Synapse, SQL Server, Snowflake, Fabric Lakehouse, Teradata - Automation & AI: Azure OpenAI, Power Automate, FastAPI, Python - AI Agents & RAG: Microsoft Foundry (Prompt Agents), Azure AI Search RAG, Fabric Data Agent, GPT-4o orchestration, NetworkX concept-graph routing - Serverless: Azure Functions (Python) for governed query tools, OpenAPI 3.0 tool registration - Modeling: Fact/Dim design, SQL optimization, Delta Live Tables, Delta MERGE - Migration: SAP ECC/HANA, JDE Oracle, Teradata/MicroStrategy, Epic EHR, DOMO/Cognos to Power BI, on-prem to cloud - Business Systems: Salesforce, Sage ERP, Yardi, Entrata, Kinaxis (Maestro), Redshift - DevOps: Azure DevOps, Git (DEV/TEST/PROD), Kubernetes, Terraform, Container Registry, Azure CLI, Entra ID SSO - Security: Managed Identity/RBAC, row-level security, masked-sandbox promotion - QA: pytest regression testing for SQL correctness and routing logic Selected Client Engagements - Manufacturing: Avoided a costly SAP ECC/HANA upgrade by modernizing directly onto Microsoft Fabric — replaced fragmented SAP/Salesforce/SharePoint reporting with Medallion architecture and Direct Lake analytics. - Insurance / Home Care: Migrated Domo/Tableau to Power BI on Fabric — rebuilt semantic models and refresh schedules, adding Copilot/AI analytics inside Teams and SharePoint. - Manufacturing: Migrated JD Edwards (JDE) Oracle reporting into a Fabric Lakehouse with Copilot-assisted SQL transformation — cut IT dependency with self-service, AI-driven insights. - Healthcare / Academic Medical Center: Unified Epic EHR and on-prem Oracle sources into one Fabric Lakehouse — consolidated fragmented clinical/operational reporting. - Real Estate Investment & Asset Management: Consolidated 12+ management companies' property, treasury, and document systems (Yardi, Entrata, JPMorgan, Chatham Financial) into one governed Fabric lakehouse — cut new-entity onboarding from weeks to hours. - Healthcare / Consumer Health Manufacturing: Integrated Kinaxis (Maestro) planning data with ERP/JDE execution data on Fabric, adding a RAG-grounded AI agent for natural-language Q&A — replaced manual root-cause analysis. Why Work With Me - Direct-sourcing model: $250/hr value for $85/hr - 100% in-house team of 50+ top problem solver engineers — no juniors, no outsourcing - Proven track record: delivering enterprise data platforms 10X faster than competitors - Direct relationship with Microsoft funding teams — helping clients tap into available funds to offset implementation costs - Ability to optimize Azure costs down by up to 83%, driving long-term savings - Building enterprise-grade AI agents with RAG, governed deterministic tools, and full auditability — not just prototypes - Hands-on leadership: I code, lead execution, own quality control and delivery - Honest, trustworthy, and committed to 100% job delivery Keywords: Azure data architect, Microsoft Fabric expert, Data Engineering, ADF pipeline developer, Power BI specialist, Databricks developer, ETL automation, SQL warehouse architect, Azure AI Search RAG, Fabric Data Agent, GPT-4o integration, Generative AI developer, LLM orchestration, AI agent architect, API Integration, Apache Spark developer, Snowflake integration, C# developer, SAP to Fabric migration, JDE migration, Epic EHR integration, Kinaxis integration, Salesforce Redshift, Sage ERP, Yardi Entrata

Top Rated Plus, top 1% on Upwork, 10+ years running production infrastructure for US companies. I am a DevOps and cloud infrastructure engineer. I design, automate, and run production environments on AWS, GCP, and Azure, and I take teams from manual deployments and "it works on my machine" to a repeatable, monitored, cost controlled platform they can ship to every day. Most of my clients come back for a second and third engagement, and many of the long running ones started as a single small task. I would rather tell you a scope is unrealistic before we start than discover it together halfway through. 𝗪𝗵𝗮𝘁 𝗜 𝗱𝗼 ▸ Cloud infrastructure: AWS (EKS, ECS, Fargate, Lambda, VPC, IAM, Aurora, RDS, S3, CloudFront), GCP (GKE, Cloud Armor, managed databases), Azure (Azure DevOps, AKS), Oracle Cloud ▸ Kubernetes: cluster design and management, Helm charts, HPA autoscaling, NGINX and Traefik ingress, Rancher, multi environment setups on GCP and AWS ▸ Infrastructure as Code: Terraform, Ansible, AWS CloudFormation, Puppet, Chef ▸ CI/CD: GitHub Actions, GitLab CI, Jenkins, CircleCI, Azure Pipelines, AWS CodePipeline, CodeBuild, CodeDeploy, TeamCity ▸ Monitoring and observability: Prometheus, Grafana, ELK, CloudWatch, New Relic, Nagios, Telegraf, InfluxDB, alerting and on call runbooks ▸ Security and compliance: HIPAA and SOC 2 aligned infrastructure, IAM hardening, VPN, network segmentation ▸ Migrations: on prem and VMware workloads to cloud, monoliths to containers, performance tuning and cost reduction after the move ▸ Linux and scripting: RHEL and Ubuntu administration, Bash and Python automation 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 I also write backend code (Python with Flask and Django, Go, JavaScript/TypeScript, Java) when the infrastructure work needs it. That means I can fix the application side of a deployment problem, build internal tooling, or wire up serverless functions myself instead of handing it back to your developers. 𝗪𝗵𝗲𝗿𝗲 𝗜 𝗵𝗮𝘃𝗲 𝗱𝗼𝗻𝗲 𝘁𝗵𝗶𝘀 ▸ Zazmic Inc, San Francisco: GCP platform built on Terraform and Ansible, GitLab CI pipelines, Helm based deployments, Cloud Armor and HPA for resilience ▸ Tripleseat, Concord MA: Azure and GCP environments, Azure DevOps pipelines, Docker, Grafana and Prometheus monitoring ▸ Century Communities, Greenwood Village CO: AWS and Oracle Cloud, ECS and EKS workloads, CircleCI, GitHub Actions and CodePipeline, Lambda and Ansible automation, CloudWatch 𝗪𝗵𝘆 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝘀𝘁𝗮𝘆 ▸ Honest scoping: you get a written scope, timeline, and the risks I see before any hours are billed. If something is out of my depth I say so. ▸ Your infrastructure stays yours: everything lives in your accounts and your repos, with documentation and handover notes so nobody depends on me to keep the lights on. ▸ Steady communication: regular progress updates in your channel of choice, no long silences, no surprises on the invoice. ▸ Production mindset: I treat your environment like I am on call for it, because during our engagement I am. That includes off hours incident response and 15 days of free support after delivery. ▸ Verifiable track record: Top Rated Plus with a 100% job success score, and I am happy to connect you with past clients for a reference. Also worked with: Docker Swarm, Docker Compose, Apache Kafka, RabbitMQ, Celery, SQS, Redis, PostgreSQL, MySQL, MongoDB, DynamoDB, Elasticsearch, AWS Elastic Beanstalk, Heroku, Serverless Framework, WordPress, Windows Server, PowerShell, .NET, Confluence #DevOps #CloudArchitect #Kubernetes #Terraform #AWS #GCP #Azure #Docker #CI_CD #InfrastructureAsCode #CloudMigration #DevOpsEngineer #Automation #CloudInfrastructure #Microservices #CloudSecurity #Serverless #AWSLambda #AzureDevOps #GitLabCI #GitHubActions #Linux #Bash #Python #Ansible #Jenkins #NGINX #ApacheKafka #Helm #EKS #GKE #Prometheus #Grafana #CloudWatch #HIPAA #SOC2 #SRE #PlatformEngineering