AI Engineer

Southern New Hampshire University is a team of innovators. World changers. Individuals who believe in progress with purpose. Since 1932,
our people-centered strategy has defined us – and helped us grow a team that now serves over 180,000 learners worldwide.

Our mission
to transform lives is made possible by talented people who bring diverse industry experience, backgrounds and skills to the university. And
today, we’re ready to expand our reach. All we need is you.

Make an impact – from near or far

We ask that our remote
employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees
must reside in, and work from, the United States.

The opportunity

Southern New Hampshire University (SNHU) is hiring
an AI Engineer to join the AI Engineering team. Reporting to AI Engineering leadership, you’ll help build and operate the AI products.
These products move SNHU’s most important learning and operational problems forward. You’ll work from inside small, embedded AI pods that
collaborate with the SNHU teams who own those problems. You’ll grow into senior ownership over time.

You’ll work under technical
direction from a Senior AI Engineer on the pod. You’ll contribute alongside the AI Analyst and Domain Product Owner. As the program scales,
you can expect to rotate across pods, which will allow patterns and practice to spread with you. Your seat is two-pronged:

You will
work 100% remotely. #LI-Remote

• AI-augmented engineering: you use AI tooling, coding agents, and modern dev workflows
  daily, are improving how you use them, and bring that practice into pod work.
• Building AI-powered products: you implement AI
  solutions: agent and orchestration components, retrieval, evaluation, and the integrations they sit inside.

What You’ll
Do:

• 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.
• entries.

Pod collaboration The canonical pod has three peers with joint accountability:

• AI Analyst – owns initiative framing, requirements craft, solution assessment, and lightweight delivery facilitation. You
  work with them to understand the requirements and user needs behind each technical task and communicate technical constraints and trade-offs
  back.
• Domain Product Owner – seated from the host team; carry domain knowledge and owns outcomes on the host side. You learn
  enough of their domain to make sound engineering trade-offs without always pinging others.
• Senior AI Engineer – sets pod-side
  technical direction and quality bar. You partner with them on architecture, scope, and quality, and grow into senior ownership over
  time.
• You will participate in discovery and shaping conversations from the start. You contribute to sprint planning, demos, and
  retros at the pace the pod sets. You bring questions and findings back to the pod as you build shared understanding of the business
  context.
• Partner with SNHU AI on governance, safety, evaluation, and adoption as they relate to your build work; follow the
  standards set at the pod and program level.
• Coordinate with IT on infrastructure, IAM, security review, and DevOps as pod work
  requires.
• Communicate progress, blockers, and resolutions to pod members and, where relevant, to host team partners.

What we’re looking for:

• 3+ years building and shipping production software at scale in one or more modern languages.
  We hire for engineering aptitude and real shipped work, not a specific stack. We use Python as our working language; we don’t require deep
  prior Python experience, but you’ll need to make yourself productive in it quickly.
• 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 . These tools have sped up your work in concrete ways, helping in certain areas while needing checking in others. Furthermore, it
  is crucial to provide evidence that you are enhancing how you use them.
• Experience working in teams or Agile delivery settings,
  including with non-engineering collaborators.

We believe real innovation comes from inclusion – where different experiences,
perspectives and talents are celebrated. So if you’re wondering whether SNHU is right for you, take the leap and apply. You might be just
the person we’re looking for.

Compensation

The annual pay range for this position is $103,577.00 – $165,754.00. Actual
offer will be based on skills, qualifications, experience and internal equity, in addition to relevant business considerations. We expect
this position to be hired in the following target hiring range $114,453.00 – $154,848.00.

Exceptional benefits (because you’re
exceptional)

You’re the whole package. Your benefits should be, too. As a full-time employee at SNHU, you’ll get:

• 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

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