Note: The job is a remote job and is open to candidates in USA. Stanbridge University is seeking a Software Engineer - AI Systems (Go) to design, build, and operate production AI systems that perform complex, multi-stage work reliably at scale. The role focuses on AI agents, durable workflows, distributed systems, model-provider integrations, backend services, testing, observability, security, and production operation.
Responsibilities
- Design, develop, test, deploy, and operate production-quality software and backend services, primarily using Go (Golang)
- Architect and build AI agents and agent-based systems capable of using tools, interacting with APIs, maintaining state and context, and executing complex multi-step workflows
- Design durable workflows that can checkpoint, resume, retry, recover, and safely continue execution following partial failures or system interruptions
- Determine how models, agents, tools, APIs, data sources, services, and deterministic application logic should divide responsibilities within an AI system, including recognizing when an AI model is not the appropriate solution
- 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 mechanisms
- Develop testing strategies for non-deterministic AI behavior using techniques such as deterministic fixtures, recorded and replayed interactions, regression suites, evaluation harnesses, and quality baselines
- Develop observability capabilities including tracing, metrics, logging, evaluation data, and replayable execution histories to support production debugging and performance analysis
- Design human-in-the-loop workflows incorporating review, approval, intervention, and modification of workflow state
- 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 other external content
- Optimize systems for reliability, latency, throughput, scalability, output quality, and cost per execution
- Build reusable engineering patterns and shared components that simplify the addition of new agents, model providers, tools, workflows, and output types
- Own technical problems from initial investigation and architecture through implementation, deployment, monitoring, troubleshooting, and ongoing production operation
- Collaborate directly with product stakeholders and domain experts to translate qualitative requirements into measurable system behavior and technical solutions
- Contribute to architectural decisions and engineering standards for AI-powered applications across the University
Skills
- 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 the ability to balance reliability, quality, performance, complexity, and cost
- Candidates must reside in an eligible state at the time of employment
- Applicants must be legally authorized to work in the United States
- Must be able to perform each essential duty satisfactorily and be physically present in the office (unless otherwise noted)
- Regularly sits for extended periods
- Physical ability to perform department-related duties
- Proficient in using electronic keyboards and office equipment
- Effective verbal communication via phone, video conferencing, and in person
- Ability to read fine print, operate computers, and understand voices clearly
- Able to lift, carry, and/or move objects weighing 10-25 pounds as needed
- Experience with AI agent frameworks, orchestration patterns, or custom agent architectures, including an understanding of when a framework may not be appropriate
- Experience with retrieval-augmented generation (RAG), embeddings, vector databases, semantic search, or knowledge-retrieval architectures
- Experience developing evaluation and observability systems for LLM applications, including tracing, regression suites, quality dashboards, or automated evaluation
- Experience with judge models, structured-output validation, evidence checking, or other AI quality-control mechanisms
- Experience designing human-in-the-loop workflows involving review, approval, intervention, or modification of active workflow state
- Experience with document processing, headless-browser rendering, text-to-speech, image generation, video generation, or other media pipelines
- Experience with event-driven architectures, durable job queues, and asynchronous processing at scale
- Experience with containers, cloud infrastructure, CI/CD, and production deployment environments
- Understanding of prompt injection, authorization boundaries, data isolation, and security considerations when untrusted content is processed by AI systems
- Experience developing systems in environments where the accuracy of generated output carries significant operational, regulatory, compliance, or safety implications
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)
Company Overview