AI Engineer

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SNHU Careers

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1932

📚 Education

🤝 Non-profit

🎯 Recruiter

Education • Non-profit • Recruitment

SNHU Careers is the careers and hiring portal for Southern New Hampshire University, a nonprofit institution focused on transforming learners’ lives. The site promotes the university’s mission-driven culture, inclusive values, employee benefits (including remote work options and paid time off), and a wide range of job categories from academics and teaching to business operations, student support, marketing, and campus roles. It encourages talent community sign-ups and highlights professional development, diversity and equity initiatives, and flexible work arrangements.

📋 Description

• Build agent orchestration, tool use, memory, retrieval, and the integrations that connect AI solutions to SNHU systems of record and data, under the technical direction of the pod's Senior AI Engineer. • Participate in architecture, prompt design, and evaluation discussions - bring your perspective, contribute to Architectural Decision Records, and grow into ownership over time. • Implement and operate solution-specific tests and evaluations; help maintain the instrumentation that makes offline and in-product signals actionable. • Work hands-on with agent and orchestration patterns and frameworks (LangGraph/LangChain, CrewAI, AutoGen, MCP, or similar), building judgment about which fit what kind of problem. • Surface delivery and technical risk early - flag blockers and ambiguities to the pod before they become problems. • Write clean, well-tested code the host team or sustainment owner can maintain after the pod departs. • Use AI development tools (Claude Code, Cursor, Codex, GitHub Copilot, and latest tools) daily; keep evolving how you work with them and share what's working with the team. • Pair with the host team's engineers on AI-augmented development practice as the engagement allows, helping them leave the engagement more capable, not just better served. • Contribute to the standard pod artifact set, which includes Agent Design Briefs, ADRs, Evaluation Scorecards, Deployment and Operations Runbooks, and retros. • Ensure that your contributions meet a quality bar that lets the next pod and the next domain team reuse what you built. • Lift what generalizes into shared AI Engineering assets - prompt and skill libraries, evaluation templates, reference architectures, practice handbook entries.

🎯 Requirements

• 3+ years building and shipping production software at scale in one or more modern languages. • Production experience in at least one major cloud (AWS, Azure, or GCP) - serverless compute, object storage, NoSQL. • Hands-on work with LLMs - orchestration, prompts, basic evaluation - in production or through substantial hands-on exploration. • Curiosity about and active learning in agentic frameworks (LangGraph/LangChain, CrewAI, AutoGen, and MCP). • Working understanding of LLM evaluation - running evals, interpreting results, and developing a sense of where outputs need checking. • Comfort with cloud-native development workflows - CI/CD and infrastructure-as-code concepts; able to get things running, not a specialist. • Experience with a relational database such as MySQL, PostgreSQL, or Oracle. • Active daily use of AI development tools, such as Claude Code, Cursor, Codex, and GitHub Copilot, is necessary.

🏖️ Benefits

• High-quality, low-deductible medical insurance • Low to no-cost dental and vision plans • 5 weeks of paid time off (plus almost a dozen paid holidays) • Employer-funded retirement • Free tuition program • Parental leave • Mental health and wellbeing resources