Senior AI Engineer

Job not on LinkedIn

🔥 5 minutes ago

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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

• 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.

🏖️ 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