Senior AI/ML Engineer
- Source: Workday
- Cable One
- Remote
- United States
- Full-Time
- Senior
Job Description
Job Description:
At Sparklight/Cableone and our family of brands, we keep our customers and associates connected to what matters most. For our associates, that means: a thriving and rewarding career, respect for the communities where they live and work, a focus on health and wellness, an excellent work/life balance, and an open and inclusive workplace.
We are open to hiring remote if we find the right talent in any of the following states: AL, AR, AZ, FL, GA, IA, ID, IL, IN, KS, LA, MD, MO, MS, NC, ND, NE, NM, NV, OR, OK, PA, SC, SD, TN, TX, UT.
The Senior AI/ML Engineer will serve as the technical authority for AI/ML platforms, agent architecture, Model Context Protocol (MCP) strategy, context engineering, orchestration, governance, and AI-assisted experiences within Network Intelligence. This role will define how agentic systems safely consume network data, engineering knowledge, automation capabilities, and operational intelligence. The Senior AI/ML Engineer will establish reusable architectural patterns, development standards, evaluation practices, human approval controls, and governance requirements while providing technical mentorship to AI Engineers assigned to technology-domain delivery teams. The position will partner closely with the Senior Network Automation Engineer to maintain a clear boundary between deterministic network capability development and intelligent consumption of those capabilities.
What you will do to contribute to the company’s success
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Define and own architecture and technical standards for AI/ML platforms, agent frameworks, agent harnesses, and agentic workflows.
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Define MCP strategy, server integration patterns, tool contracts, access controls, and lifecycle standards.
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Design reusable patterns for agent orchestration, multi-agent coordination, long-running workflows, and escalation paths.
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Establish standards for context engineering, memory systems, retrieval, grounding, source attribution, and knowledge packaging.
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Define human-in-the-loop approval requirements, reasoning boundaries, tool execution safeguards, auditability, and governance controls.
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Create evaluation frameworks and acceptance criteria for correctness, safety, reliability, hallucination reduction, and tool execution.
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Define how agents consume network APIs, automation services, data products, procedures, and engineering knowledge.
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Partner with the Senior Network Automation Engineer to maintain the capability contract between Network Automation Engineering and AI Engineering.
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Review complex, high-risk, or net-new AI and agentic solution designs.
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Guide AI Engineers assigned to technology-domain delivery teams and establish reusable implementation patterns.
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Provide technical mentorship, design guidance, code review, and architectural support for AI-focused engineering resources.
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Partner with Platform Engineering on AI service hosting, deployment, monitoring, alerting, scalability, and production readiness.
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Partner with Data Engineering, NMS Engineering, Reporting Engineering, and Capacity Engineering to ensure agents use trusted and appropriately structured data.
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Coordinate conversational and AI-assisted user experience requirements with UI/UX and front-end contributors.
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Produce High Level Designs (HLDs), architecture decision records, technical standards, and implementation guidance.
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Apply secure software development, CI/CD, source control, testing, and operational support practices to AI solutions.
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Evaluate emerging AI/ML, agentic, orchestration, and MCP technologies for practical enterprise adoption.
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Communicate architectural decisions, technical risks, dependencies, and recommendations to engineering and leadership stakeholders.
Education and/or Experience
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Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or a related technical field is preferred.
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Alternatively, 8 or more years of progressive experience in software engineering, platform engineering, data engineering, AI/ML engineering, or related technical disciplines will be considered.
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Five or more years of experience designing or delivering AI/ML, large language model, or agentic systems is preferred.
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Demonstrated experience leading technical architecture, establishing engineering standards, and guiding complex or net-new solution delivery.
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Strong Python development skills and experience buildi…
Skills
- attribution
- Python
- microsoft-graph
- microsoft-azure
- amazon-web-services
- amazon-machine-learning
- google-cloud-platform
- azure-databricks
- databricks
- Kubernetes
- LangGraph
- LangChain
- workday
