AI Multi-Agent Systems & Full-Stack Development | Open to Remote
Remote only
Open to work.
Recruiters read below.
Remote Positions only
AI Engineer | Backend Architecture & Cloud Infrastructure
I design and build production AI agent systems and scalable backend infrastructure.
Built production multi-agent system using LangGraph with Vertex AI (Claude and Gemini APIs) to automate scraper remediation - reduced manual fix time from full days to 10-20 minutes with human oversight, achieving 60% autonomous success rate. Implemented PII safety protocols, Datadog tracing, and observability for production LLM integration
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Remediate web scraping errors for financial institution connections maintaining reliable data aggregation across thousands of institutions and millions of member accounts
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Enhanced issue visibility and automation by building intelligent Jira system for lifecycle management - automates issue creation/closure/linking/ranking based on thresholds, Slack alerting, and deployment integration to prioritize remediation work
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Architect event-driven backend systems on GCP handling thousands of daily message queues via Pub/Sub, Cloud Scheduler, and asynchronous processing patterns using TypeScript/Node.js services
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Configure and manage production Kubernetes infrastructure using KCC, IAM, KMS encryption, External Secrets, service accounts, and secure inter-service communication
Lead Frontend Engineer on a AI/ML project that processed data using various ML and AI services within an event-driven environment creating several successful transactions for the vendor.
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Architect for frontend React components and features throughout the application achieving demands for multiple clients in separate environments.
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Deployed to self managed Kubernetes and AWS environments, updating configuration templates in terraform, while also solving possible deployment hurdles.
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Design and construction of the entire Frontend UI using React with an overall aesthetic style, and user-centric interface transforming complex data into frontend displays combined with functional architecture from development to production level.
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Create UI prototypes for stakeholders to approve and migrated into code by creating reusable React UX components and maintaining all state logic to display data.
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Integrated cloud native services on AWS including S3, SNS, SQS, EB, and cloud agnostic services using RabbitMQ, and Minio in Kubernetes to the frontend via server-side configurations to achieve all necessary frontend functionalities.
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Consolidated data upload components including multipart uploads on the frontend central to processing large datasets for ML data to be displayed within the application.
Implementation of any 3rd party APIs required for task completion including Open Ai GPT-3 models API for automation.
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Developed a brand new optimized design of main features on front end components including integrating text editing, and video editing tools to get ready for site launch.
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Optimizing components for responsive performance on desktop and tablet browsers.
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Maintaining and building reusable components for future use while creating proper type safe using mainly React Node and Typescript.
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Translating architectural design into efficient readable and reusable code using standard coding conventions.
