Systems Architect — AI, AWS & Consumer Platforms

Go Fractional; United States; A distancia; USD 124.000 - 234.000; Jornada completa

Descripción de la vacante

Go Fractional is seeking a Contract Systems Architect to translate product goals into secure, scalable systems. Work closely with founders and engineers on AWS infrastructure, AI model integration, and production readiness.

You'll move from architecture diagrams to code and deployments, balancing what to build now versus later, and ensuring designs align with business needs and cost constraints.

Formación

• Proven track record as a Systems Architect or senior technical leader delivering production software.
• Deep hands-on AWS experience and ability to explain architectural tradeoffs.
• Experience shipping consumer applications with focus on scale, availability, and cost.
• Production experience integrating LLMs and AI workflows beyond PoCs.
• Knowledge of leading models and evaluation approaches for AI workloads.
• Strong backend skills in Python or TypeScript/Node.js; related stacks.
• Understanding of AI security risks, prompt injections, and data protection.

Responsabilidades

• Assess product requirements, existing architecture, and infra; identify risks and priorities.
• Design AWS architectures for consumer apps including APIs, compute, storage, and databases.
• Evaluate AI models and providers against workloads, balancing quality, latency, privacy, and cost.
• Design AI capabilities like retrieval-augmented generation and agent orchestration where beneficial.
• Establish production controls for AI workflows, including evaluations, retries, and human approvals.
• Address authentication, data protection, traffic spikes, abuse prevention, and responsive UX needs.
• Define infrastructure as code, CI/CD pipelines, environments, monitoring, backup, and recovery.
• Collaborate with engineers on implementation and validate through prototypes or load tests.
• Document decisions and provide handoffs for independent operation and extension.

Conocimientos

Systems Architect

AWS

Python

TypeScript/Node.js

Containers / Serverless

AI/ML Workflows

Security & Compliance

Herramientas

AWS

Python

TypeScript/Node.js

Containers

Descripción del empleo

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

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.