Contract Systems Architect — AI, AWS & Consumer Platforms

MarcoPolo Learning, Inc.; United States; Remote; USD 165,000 - 262,000; Full time

Job summary

MarcoPolo Learning, Inc. is seeking a Contract Systems Architect to guide AI, AWS, and consumer platform architecture. You will translate product goals into secure, scalable, and cost-effective systems, with hands-on coding and production readiness.

You will work with founders and engineers across architecture reviews, AI model integration, and deployment pipelines, delivering prototypes, controlled experiments, and thorough handoff documentation for independent team operation.

Qualifications

• Experience as Systems Architect or senior technical leader building production software.
• Deep hands-on AWS experience and ability to explain tradeoffs.
• Production experience shipping consumer applications with scalable infra costs.
• Experience integrating LLMs and building AI workflows beyond proofs of concept.
• Knowledge of leading models and evaluating releases.
• Strong backend skills in Python or TS/Node.js.

Responsibilities

• Assess product requirements, architecture, and priorities.
• Design AWS architectures for consumer apps: APIs, compute, storage, DBs, caching, queues, async processing.
• Evaluate AI models and providers for quality, latency, reliability, privacy, cost.
• Design AI capabilities like retrieval-augmented generation and agent orchestration.
• Establish production controls for AI workflows with evaluations, tracing, retries, fallbacks, human approvals.
• Address consumer platform needs: auth, data protection, traffic spikes, abuse prevention, user experience.
• Define infrastructure as code, pipelines, environment separation, monitoring, backup, recovery.
• Collaborate with engineers, review code/infrastructure changes, validate via prototypes/load testing.
• Document decisions and enable handoff for operations.

Skills

AWS expertise

Production systems

Python

TypeScript/Node.js

Relational databases

Caching

Messaging

Containers

Serverless

Infrastructure as code

AI security

LLMs integration

Model evaluation

Job description

Contract Systems Architect - AI, AWS & Consumer Platforms

Engagement: Project-based independent contractor

Location: Remote, worldwide; North American time zones preferred

Schedule: Flexible, with agreed overlap with our team

Compensation: Hourly or fixed project fee, based on scope and experience

About us

We're an AI-focused consumer technology startup building products designed to reach a large user base. We're looking for an experienced Systems Architect to help us make practical technical decisions, deliver reliable AI capabilities, and establish infrastructure that can grow with the business.

This is a project-based contract role. Each engagement will have an agreed scope, timeline, deliverables, and acceptance criteria. Follow-on projects may be available as our needs evolve.

The role

You'll work directly with founders and engineers to translate product goals into secure, scalable, and cost-effective systems. Your work may span architecture reviews, AWS infrastructure, AI model integration, agentic workflows, and production readiness.

You should be comfortable moving from architecture diagrams to code, prototypes, infrastructure configuration, and technical reviews. We value clear judgment: knowing what to build now, what to defer, and when a simpler design will serve the business better.

What you'll do

• Assess our product requirements, existing architecture, and infrastructure; identify risks, bottlenecks, and priorities.
• Design AWS architectures for consumer applications, including APIs, compute, storage, databases, caching, queues, and asynchronous processing.
• Evaluate AI models and providers against representative workloads, balancing output quality, latency, reliability, privacy, and cost.
• Design AI capabilities such as retrieval-augmented generation, structured outputs, tool use, and agent orchestration where they improve the product.
• Establish production controls for AI workflows, including evaluations, tracing, execution limits, retries, fallbacks, and appropriate human approval.
• Address consumer platform needs such as authentication, authorization, user data protection, traffic spikes, abuse prevention, and responsive user experiences.
• Define infrastructure as code, deployment pipelines, environment separation, monitoring, backup, and recovery practices.
• Partner with engineers on implementation, review critical code and infrastructure changes, and validate key assumptions through prototypes or load testing.
• Document decisions and provide a clear handoff so our team can operate and extend the systems independently.

What you'll bring

• A strong track record as a Systems Architect, Staff/Principal Engineer, or technical leader building and operating production software.
• Deep hands-on AWS experience and the ability to explain service choices and architectural tradeoffs.
• Experience shipping consumer applications and managing growth, availability, performance, and infrastructure costs.
• Production experience integrating LLMs and building AI workflows beyond demonstrations or proofs of concept.
• Current knowledge of leading commercial and open-weight models, with a repeatable approach to evaluating new releases.
• Strong backend engineering skills in Python, TypeScript/Node.js, or comparable languages.
• Experience with relational databases, caching, messaging, containers or serverless systems, and infrastructure as code.
• Practical understanding of AI security risks, including prompt injection, sensitive data exposure, and excessive tool permissions.
• Clear written communication, reliable project estimation, and experience delivering independently within an agreed scope.

Useful additional experience

• Early-stage startups with small engineering teams.
• Amazon Bedrock and direct model-provider APIs.
• Agent frameworks and Model Context Protocol (MCP) integrations.
• Retrieval systems, vector search, personalization, or multimodal AI.
• Model routing, inference optimization, and cost measurement per user or completed task.

Typical project deliverables

Depending on the engagement, deliverables may include:

• An architecture assessment and prioritized recommendations.
• A target architecture, documented tradeoffs, and phased implementation plan.
• Working prototypes or production components for critical capabilities.
• Infrastructure code, deployment configuration, and operational runbooks.
• Performance, reliability, AI quality, and cost benchmarks.
• Engineering handoff documentation and knowledge-transfer sessions.

Success means delivering systems that meet agreed requirements, fit our stage and budget, and can be maintained by our team.

Candidates worldwide are welcome. North American time zones are preferred, but we're open to candidates elsewhere who can provide suitable working-hour overlap.