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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Platform Engineer - **Company:** GIVZEY, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Cloud Computing, Cloud Engineering, Databases, Continuous Integration, Software Debugging, DevOps, Programming Tools, Disaster Recovery, Github, Identity and Access Management, Python (Programming Language), PostgreSQL, Redis, Search Technologies, AI Infrastructure, Pulumi, Delivery Pipeline, Large Language Models, Reliability of Systems, Generative AI, Amazon Virtual Private Cloud (VPC), Backend, Cloudformation, Event Driven Architecture, AI Platforms, Infrastructure Automation Frameworks, Machine Learning Operations, Api Design, Cloudwatch, Amazon Simple Queue Service (SQS), Terraform, New Relic (SaaS), Docker - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/ai-platform-engineer-givzey-8733877 ## About the Role * 5+ years building and operating production software systems * Strong experience with AWS in production environments * Experience designing Infrastructure as Code using Pulumi, Terraform, or CloudFormation * Experience building CI/CD pipelines using GitHub Actions * Strong Python experience * Experience building APIs and backend systems Cloud & Platform You should be comfortable working with technologies such as: * AWS (multi-account environments using AWS Organizations) * ECS * Docker * IAM * VPC networking * RDS * S3 * Lambda * CloudWatch * SNS/SQS * Event-driven architectures AI Infrastructure Experience with some of the following is highly desirable: * Amazon Bedrock * SageMaker * Vector databases * Retrieval-Augmented Generation (RAG) * LLM evaluation pipelines * Model deployment * ML infrastructure * Dagster or similar orchestration platforms Working Style * You automate repetitive work instead of documenting it. * You care about reliability as much as shipping features. * You enjoy improving developer experience. * You think systems should become simpler over time. * You take ownership rather than waiting for someone else to fix infrastructure problems. Mindset * Strong written communication. * Comfortable working in ambiguity. * Curious about modern AI infrastructure and where it's headed. * Interested in building systems that engineers enjoy working in. * Excited by the challenge of building infrastructure from the ground up rather than inheriting a mature platform., * Pulumi experience * Dagster experience * Amazon Bedrock * SageMaker * OpenSearch * ECS * PostgreSQL * Redis * New Relic or modern observability platforms * Experience supporting AI or ML products * SOC 2 or security/compliance experience * Startup experience ## Description This role owns the platform that keeps Givzey secure, compliant, reliable, and scalable. You'll work across AWS infrastructure, Infrastructure as Code, CI/CD, AI services, observability, and developer tooling to make sure engineers spend their time building product instead of fighting deployments. You'll partner closely with engineering, ML, and product to design the platform that powers everything from customer-facing APIs to LLM workflows running on Amazon Bedrock and SageMaker. This is not a "keep the lights on" devops role. You'll actively shape how we deploy software, provision infrastructure, manage AI workloads, and scale the engineering organization., You're the engineer who gets excited about replacing a manual deployment with a one-click pipeline, automating infrastructure instead of clicking around the AWS console, and designing systems that make the rest of engineering move faster. You think in terms of reliability, observability, automation, and repeatability. You're comfortable wearing multiple hats. One morning you might be debugging IAM permissions. That afternoon you're building a Pulumi module, improving GitHub Actions, tuning ECS workloads, or helping an ML engineer deploy a SageMaker endpoint. What you'll do Cloud infrastructure * Design, build, and maintain our AWS infrastructure * Manage networking, IAM, compute, storage, databases, and security across environments * Build scalable infrastructure capable of supporting rapid product growth * Improve resiliency, availability, and disaster recovery Infrastructure as Code * Own our Infrastructure as Code strategy using Pulumi * Build reusable infrastructure components and shared modules * Eliminate manual infrastructure changes wherever possible * Review and evolve our cloud architecture as the company grows CI/CD * Build and maintain deployment pipelines for applications and infrastructure * Improve release automation and deployment safety * Reduce friction in local development and engineering workflows * Help establish engineering best practices around testing and deployment AI Platform * Build and maintain the infrastructure powering our AI systems * Work with services such as Amazon Bedrock, SageMaker, OpenSearch, and supporting AWS services * Support LLM evaluation pipelines, RAG infrastructure, vector search, and model deployment * Partner with ML engineers to operationalize new AI capabilities Platform Operations * Monitor production systems and improve observability * Respond to production incidents and drive root-cause analysis * Improve system reliability through automation rather than manual processes * Continuously evaluate performance, cost, and scalability Engineering * Collaborate closely with product, engineering, ML, and customer success * Help define technical standards and infrastructure direction * Participate in architecture discussions across the platform * Mentor other engineers on cloud infrastructure and operational best practices ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Why segmenting your infrastructure into tiers makes your infrastructure design better](https://www.wearedevelopers.com/videos/1960-why-segmenting-your-infrastructure-into-tiers-makes-your-infrastructure-design-better) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Unleashing Potential Across Teams: The Power of Infrastructure as Code](https://www.wearedevelopers.com/videos/930-unleashing-potential-across-teams-the-power-of-infrastructure-as-code) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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