Software Engineer – AI Systems, Go

🔥 1 minute ago

🌵 Arizona, Colorado, +15 more states – Remote

🌵 Arizona – Remote ⛰️ Colorado – Remote 🌽 Illinois – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote ⚜️ Louisiana – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🌲 North Carolina – Remote 🌾 North Dakota – Remote 🏈 Ohio – Remote 🦀 Maryland – Remote 🚗 Michigan – Remote ❄️ Minnesota – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote 🧀 Wisconsin – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Stanbridge University

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1996

📚 Education

🏥 Healthcare

Education • Healthcare

Stanbridge University is a private institution of higher education focused on allied health professions and nursing. It offers accredited, licensure-oriented programs including vocational nursing (LVN), Bachelor of Science in Nursing (BSN), Master of Science in Nursing (MSN-Ed), Master of Science in Occupational Therapy (MSOT), Occupational Therapy Assistant (OTA), and Physical Therapist Assistant (PTA), delivered across multiple Southern California campuses (Orange County, Los Angeles, Riverside, San Diego) and online. The school emphasizes academic rigor, innovation and education technology, student support services, and preparation for professional licensure (notably high NCLEX-RN pass rates reported for several campuses). Stanbridge also highlights community outreach, alumni services, and awards/recognition from organizations such as the Carnegie Classification and external rankings.

📋 Description

• Design, develop, test, deploy, and operate production-quality software and backend services, primarily using Go • Architect and build AI agents and agent-based systems using tools, APIs, state, and context for complex multi-step workflows • Design durable workflows that checkpoint, resume, retry, recover, and continue safely after failures or interruptions • Determine responsibilities across models, agents, tools, APIs, data sources, services, and deterministic application logic • Design integrations across multiple AI model providers, including routing, failover, rate-limit management, health monitoring, and degradation strategies • Build safeguards including structured-output validation, error handling, retries, quality gates, evidence validation, and automated recovery • Develop testing strategies for non-deterministic AI behavior using fixtures, recorded/replayed interactions, regression suites, evaluation harnesses, and quality baselines • Develop observability through tracing, metrics, logging, evaluation data, and replayable execution histories • Design human-in-the-loop workflows incorporating review, approval, intervention, and workflow-state modification • Build and maintain APIs, backend services, relational data models, job-processing infrastructure, and supporting application components • Develop secure methods for ingesting and processing user-supplied documents and external content • Optimize reliability, latency, throughput, scalability, output quality, and cost per execution • Build reusable patterns and shared components for agents, model providers, tools, workflows, and output types • Own technical problems from investigation and architecture through implementation, deployment, monitoring, troubleshooting, and production operation • Collaborate with product stakeholders and domain experts to translate requirements into measurable behavior and technical solutions • Contribute to architectural decisions and engineering standards for AI-powered applications across the University • Build reliable production AI workflows, improve measurability and quality, reduce latency and cost, and establish foundational AI engineering practices

🎯 Requirements

• Substantial professional experience developing and operating production software, with strong experience in Go (Golang) or demonstrated depth in another backend language with the ability to become productive in Go quickly • Hands-on experience shipping an LLM-backed application, AI agent, or agent-based system into production and supporting it after deployment • Strong understanding of AI application architecture, including how models, agents, tools, APIs, data sources, services, and application logic interact • Demonstrated distributed-systems engineering knowledge, including concurrency, asynchronous processing, queues, idempotency, retries, partial failure, state management, and recovery • Experience designing systems that remain reliable when individual services, providers, or workflow stages fail • Demonstrated testing discipline for systems involving non-deterministic behavior • Strong experience designing and consuming HTTP APIs • Experience with relational databases, SQL, and persistent application state • Experience building, deploying, monitoring, and troubleshooting backend services in production environments • Understanding of software architecture, testing, debugging, observability, and production engineering practices • Ability to independently own ambiguous technical problems from investigation through production implementation • Strong analytical judgment and ability to balance reliability, quality, performance, complexity, and cost • Applicants must be legally authorized to work in the United States • Must reside in an eligible state at the time of employment • Official transcripts are required prior to hire • Degrees earned outside the United States must be evaluated by a recognized credential evaluation service • Must be able to perform each essential duty satisfactorily and meet stated physical requirements • Preferred: experience with AI agent frameworks, RAG, embeddings, vector databases, semantic search, LLM evaluation and observability, judge models, structured-output validation, human-in-the-loop workflows, media pipelines, event-driven architectures, containers, cloud infrastructure, CI/CD, prompt injection, authorization boundaries, data isolation, and security considerations

🏖️ Benefits

• Health Care Plan (Medical, Dental & Vision) • Retirement Plan (401k) • Exciting university events • Seasonal motivational health and wellness challenges • Work/Life Balance initiatives • Onsite wellness program / Staff Chiropractor • Life Insurance (Basic, Voluntary & AD&D) • Paid Time Off (Vacation, Sick & Public Holidays) • Family Leave (Maternity, Paternity) • Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions