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Job Description
Junior AI Systems Engineer Buildable AI Lake Forest, CA Job Details Part-time | Full-time | Contract $73,436.99 - $88,440.25 a year 3 hours ago Qualifications AI models System troubleshooting Databases JavaScript Systems engineering Developing and maintaining backend systems
TypeScript Full Job Description Company:
Buildable Ai (buildable.global)
Role:
Junior AI Systems Engineer The Reality Check (Read Before Applying) Do not let the "Junior" title fool you. This is an execution-heavy role for someone who is already highly fluent in AI-assisted development. Do not apply if you are an absolute beginner to AI systems. We expect you to already know how to use AI tools to write, debug, and ship code at a high velocity. We are looking for an emerging expert who understands the fundamentals of how these models work and is ready to refine complex systems under the guidance of senior leadership. About the Role As a Junior AI Systems Engineer at Buildable Ai, you will be the boots on the ground for our core technology refinement. Working directly under our Senior Engineers, you will be in the trenches making sure our AI systems are talking to each other effectively. You will be responsible for implementing integrations, testing system outputs, and using AI tools to write the connective tissue that powers our platform.
Core Responsibilities Systems Integration:
Write the reliable, scalable code that links our internal AI models with external tools, APIs, and databases.
AI-Assisted Execution:
Use the latest AI coding assistants to write clean code rapidly, taking raw architectural concepts and turning them into functional features for buildable.global.
Testing & Refinement:
Rigorously test AI workflows, identify hallucinations or communication breakdowns between systems, and implement fixes to improve accuracy.
Continuous Learning:
Stay hyper-current on the bleeding edge of AI tools and models, bringing new efficiency strategies to the engineering team.
Mandatory Qualifications Demonstrable AI Experience:
A strong portfolio of personal projects, open-source contributions, or past roles where you heavily integrated AI/LLM APIs.
Solid Programming Foundation:
Strong skills in backend languages (Python, JavaScript/TypeScript) and a deep comfort level with debugging complex, multi-system issues. Fluency in
AI Tools:
You must already use AI tools daily to accelerate your coding process and troubleshoot errors.
Analytical Problem Solving:
An obsessive curiosity about how AI systems communicate and a persistent drive to refine those workflows.