Senior AI Engineer

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đŸ”„ 15 hours ago

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Logo of SNHU Careers

SNHU Careers

10,000+ employees

Founded 1932

📚 Education

đŸ€ 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

‱ Design and ship AI solutions - agent orchestration, tool use, memory, retrieval, and the integrations that connect them to SNHU systems of record and data. ‱ Oversee architectural decisions and their documentation (Architectural Decision Records), making choices the host team or sustainment owner can maintain after the pod departs. ‱ Design and operate solution-specific tests and evaluations; build the instrumentation that makes offline and in-product signals actionable. ‱ Implement agent and orchestration patterns using frameworks like LangGraph/LangChain, CrewAI, AutoGen, MCP, or custom approaches choosing pragmatically based on what the solution and the host environment can sustain. ‱ Surface delivery and technical risk early; make scope and architecture trade-offs decisively rather than letting them drift. ‱ Use AI development tools like Claude Code, Cursor, Codex, GitHub Copilot, and latest tools as a daily part of how you ship. ‱ Maintain a clear point of view on where they help, where they fail, and how to validate their output. ‱ Pair with the host team's engineers on AI-augmented development practice, so they leave the engagement more capable, not just better served. ‱ Produce the standard pod artifact set, which includes Agent Design Briefs, ADRs, Evaluation Scorecards, Deployment and Operations Runbooks, and retros. ‱ Ensure the quality bar is high enough to allow the next pod and the next domain team to reuse what you built. ‱ Contribute to shared AI Engineering assets - prompt and skill libraries, evaluation templates, reference architectures, practice handbook entries - that codify what works and increase capabilities across the team.

🎯 Requirements

‱ 5+ years shipping and operating production software at scale in one or more modern languages. ‱ Production experience in at least one major cloud (AWS, Azure, or GCP). ‱ Hands-on production work with LLMs - orchestration, memory, tool use, evaluation. ‱ Experience designing agentic systems. ‱ Familiar with at least one framework, such as LangGraph/LangChain, CrewAI, AutoGen, MCP, or a custom approach. ‱ Practical LLM evaluation - designing evals, reading offline vs. in-product signals, building the instrumentation to act on them. ‱ Infrastructure as Code (CDK, Terraform, or similar) and CI/CD (GitHub Actions or similar) - self-sufficient, not a specialist. ‱ Experience with a relational database such as MySQL, PostgreSQL, or Oracle. ‱ Demonstrated hands-on proficiency with AI-assisted development tools, such as Claude Code, Cursor, Codex, and GitHub Copilot. ‱ Ability to guide and validate outputs to avoid and detect issues that can impact results. ‱ Experience translating ambiguous domain problems into shipped systems with non-engineering partners.

đŸ–ïž 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

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