About the role

What will you do at fullthrottle.ai®?

As a fully remote, fast-growing startup, we move quickly, embrace innovation,

and follow an Agile/Scrum framework to deliver impactful solutions. We're

looking for someone who thrives in a collaborative environment, enjoys solving

complex technical challenges, and wants to help build and scale the future of AI

at fullthrottle.ai.

The Role

As our AI Platform Engineer, you will ensure the reliable, secure, and scalable

deployment of AI systems across fullthrottle’s platforms. You’ll focus on

building and managing production infrastructure, developing robust APIs and

microservices, and optimizing for cost-effective operations. This role requires

hands-on expertise in AI/ML platform engineering, production deployment of AI

systems, infrastructure as code, and cloud-native engineering to deliver

high-performance AI solutions.

You will play a pivotal role in implementing best practices for deploying,

operating, and scaling AI/ML systems in production, defining infrastructure as

code for AWS, and driving observability and optimization across our AI

production environments.

Key Responsibilities

* API & Microservices Development: Build and manage production-grade APIs and
microservices to support scalable AI deployments.
* AI Agent Development: Build, tune, and deploy AI agents using Amazon Bedrock
AgentCore Runtime and the Strands Agent SDK. Design system prompts, implement
tool routing, and optimize for latency and accuracy.
* Infrastructure as Code: Define and manage Terraform modules for AWS services
(Lambda, S3, RDS, OpenSearch, etc.).
* Observability & Monitoring: Monitor system performance and implement
observability practices using tools such as New Relic, Cloudwatch, and
OpenTelemetry to ensure reliability, proactive alerting, and rapid issue
resolution.
* CI/CD Pipelines: Build and maintain CodePipeline/CodeBuild pipelines for
automated testing, Docker builds, and ECS deployments.
* Optimization: Optimize infrastructure and operations for cost, latency, and
reliability, ensuring efficient use of resources.
* Compliance & Security: Ensure systems meet compliance standards
and maintain robust security controls.
Required

Qualifications

* Experience: Minimum 2+ years of hands-on AI engineering experience, including
building and deploying scalable infrastructure for AI/ML systems.
* Technical Expertise: Expert-level Python and AWS (Lambda, API Gateway,
CloudWatch).
* AI/ML Experience: Hands-on experience with AI/ML systems, including model
integration, inference workflows, or lightweight model development, along
with Amazon Bedrock (including AgentCore Runtime), LLM prompt engineering, or
agent frameworks. Must be comfortable building and iterating on AI/ML-driven
application logic and agent workflows in production.
* Infrastructure as Code: Strong experience with Terraform and/or
CloudFormation for AWS resource management.
* Production Experience: Proven ability to operate large-scale, multi-tenant
SaaS architectures in production.
* Monitoring & Optimization: Deep understanding of system monitoring, cost
optimization, and compliance in cloud environments.
* Education/Certifications: Bachelor’s degree in Computer Science, Data
Engineering, or a related field. Relevant certifications in AWS or DevOps are
a plus.
* Collaboration: Proven ability to work effectively in cross-functional teams
and communicate technical concepts to non-technical stakeholders.
You're Not a Fit If...
* You haven’t previously built and managed production-grade APIs or
infrastructure for AI systems.
* You are not an expert in Python and/or AWS.
* You prefer a slow-moving environment and are not comfortable with the pace of
a startup.
* You prefer to react to problems rather than plan ahead strategically.
* You do not want to be hands-on with the technical details of the role.
Our Core Principles:
We're a team that believes in big ideas and fast execution, adopting a "crawl,
walk, run" approach to innovation. We're looking for someone who embodies these
principles:
* Customer Centricity: We always put our customers first.
* Growth Mindset: We are constantly learning and evolving.
* Accountability & Integrity: We take ownership and act with honesty.
* Collaboration & Humility: We work together and value every voice.
* Open Communication: We believe in transparency and direct feedback.
If you are a passionate, experienced AI platform engineer with a drive to build
and optimize advanced AI infrastructure, we want to hear from you. This is an
opportunity to make a real impact at a dynamic and growing company.

Which skills does this role require?

TerraformAmazon BedrockAPI DevelopmentMicroservicesInfrastructure as CodeCI/CDLLM Prompt EngineeringDockerECSObservabilityNew RelicCloudWatchOpenTelemetrySaaS ArchitectureAI Platform EngineeringMachine LearningAWS LambdaAPI GatewayAgentCore RuntimeStrands Agent SDKCloudFormationS3RDSOpenSearchCodePipelineCodeBuildSaaSAgileScrumPrompt EngineeringCloud-NativeCost OptimizationComplianceLLMsDesign Systems

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