Senior AI/ML Engineer

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

• Define and own architecture and technical standards for AI/ML platforms, agent frameworks, agent harnesses, and agentic workflows.

• Define MCP strategy, server integration patterns, tool contracts, access controls, and lifecycle standards.

• Design reusable patterns for agent orchestration, multi-agent coordination, long-running workflows, and escalation paths.

• Establish standards for context engineering, memory systems, retrieval, grounding, source attribution, and knowledge packaging.

• Define human-in-the-loop approval requirements, reasoning boundaries, tool execution safeguards, auditability, and governance controls.

• Create evaluation frameworks and acceptance criteria for correctness, safety, reliability, hallucination reduction, and tool execution.

• Define how agents consume network APIs, automation services, data products, procedures, and engineering knowledge.

• Partner with the Senior Network Automation Engineer to maintain the capability contract between Network Automation Engineering and AI Engineering.

• Review complex, high-risk, or net-new AI and agentic solution designs.

• Guide AI Engineers assigned to technology-domain delivery teams and establish reusable implementation patterns.

• Provide technical mentorship, design guidance, code review, and architectural support for AI-focused engineering resources.

• Partner with Platform Engineering on AI service hosting, deployment, monitoring, alerting, scalability, and production readiness.

• Partner with Data Engineering, NMS Engineering, Reporting Engineering, and Capacity Engineering to ensure agents use trusted and appropriately structured data.

• Coordinate conversational and AI-assisted user experience requirements with UI/UX and front-end contributors.

• Produce High Level Designs (HLDs), architecture decision records, technical standards, and implementation guidance.

• Apply secure software development, CI/CD, source control, testing, and operational support practices to AI solutions.

• Evaluate emerging AI/ML, agentic, orchestration, and MCP technologies for practical enterprise adoption.

• Communicate architectural decisions, technical risks, dependencies, and recommendations to engineering and leadership stakeholders.

Education and/or Experience

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or a related technical field is preferred.

• 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.

• Five or more years of experience designing or delivering AI/ML, large language model, or agentic systems is preferred.

• Demonstrated experience leading technical architecture, establishing engineering standards, and guiding complex or net-new solution delivery.

• Strong Python development skills and experience building production-grade services and integrations.

• Experience with large language models, agent frameworks, tool calling, retrieval-augmented generation, context engineering, and model evaluation.

• Experience designing MCP servers, MCP clients, or comparable tool-integration architectures is strongly preferred.

• Experience with REST APIs, event-driven integrations, structured data, and enterprise system integration.

• Experience with vector databases, graph databases, knowledge graphs, semantic retrieval, or metadata-driven knowledge systems.

• Experience with cloud-based AI services, containerized deployment, Git, CI/CD, testing, monitoring, and production support.

• Experience applying security, governance, human approval, auditability, and responsible AI practices to production systems.

• Experience in telecommunications, ISP, network engineering, infrastructure, or operational technology environments is preferred.

Certificates, Licenses, Registrations

Specific Certifications are not required. There are a few that can demonstrate significant understanding of key concepts.

• Microsoft Certified: Azure AI Engineer Associate

• Microsoft Certified: Azure Solutions Architect Expert

• Microsoft Certified: DevOps Engineer Expert

• AWS Certified Machine Learning Engineer - Associate or AWS Certified Machine Learning - Specialty

• Google Cloud Professional Machine Learning Engineer

• Databricks Certified Machine Learning Professional

• Certified Kubernetes Application Developer or Certified Kubernetes Administrator

• Relevant responsible AI, cloud security, data engineering, or architecture certifications

Other Qualifications

• Demonstrated ability to distinguish deterministic automation responsibilities from agentic orchestration and AI-consumption responsibilities.

• Experience establishing reusable agent architectures, development standards, governance patterns, and evaluation methods.

• Experience with MCP, Semantic Kernel, LangGraph, LangChain, Azure AI services, Azure OpenAI, or comparable agent and orchestration frameworks.

• Experience with retrieval-augmented generation, embeddings, vector search, graph-based retrieval, and knowledge packaging.

• Understanding of AI safety, hallucination reduction, prompt injection risks, tool-use controls, auditability, and human approval patterns.

• Ability to evaluate AI-generated outputs and agent actions for correctness, safety, reliability, and operational impact.

• Ability to translate engineering procedures, operational knowledge, and business processes into governed agentic workflows.

• Ability to communicate complex architecture, risks, tradeoffs, and technical recommendations to technical and non-technical stakeholders.

• Strong technical leadership, mentoring, problem-solving, and cross-functional collaboration skills.

• Ability to work effectively with Network Automation Engineers, Platform Engineers, Data Engineers, NMS Engineers, Reporting Engineers, Capacity Engineers, Network Security, and Infrastructure Engineering.

• Adaptability and willingness to evaluate emerging AI technologies while maintaining disciplined production standards.

• Ownership mindset and accountability for architecture quality, production readiness, governance, and delivery outcomes.

• Position may require occasional on-call availability.

• Position may require up to 10% travel.

Benefits

Cable One and our family of brands appreciates the role our associates play to help the company grow, and in return an excellent benefits package is offered to our associates to recognize the importance of their contributions, such as:

• Medical, dental, and vision plans - start when you start!
• Life insurance (self, spouse, children)
• Paid time off (vacation, holiday, and personal/sick days)
• 401(k) - 100% company match starts day 1 of employment (up to 5% of eligible compensation)
• Group Legal plan with Identity Theft Protection

Additional Perks

• Tuition reimbursement (up to $5,250 on 1st year)
• Annual community support to various organizations across the U.S.
• Associate recognition & awards programs
• Advancement opportunities
• Collaborative work environment
• FREE Cable One services for associates who live in a serviceable area
• Up to $75/mo. Stipend
• Remote Access to select premium channels (Cable One, Sparklight, Cable America and ValueNet Fiber Only)
• Vehicle provided for daily work purposes, if residing within reasonable radius from office location

Our Commitment

Diversity lies in the communities we serve and among the associates who dedicate themselves to ensure our continued success. Here at Cable One and our family of brands, we believe it is our individual and unique talents, backgrounds and perspectives that, when combined, truly make us an unstoppable force. "Stronger Together" is not just a verbal cue, it is the motto that our associates live by, exemplify, and embody each and every day.

Cable One and our family of brands is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a protected veteran, or disability.

Pre-hire Processes

Cable One and our family of brands is committed to keeping our associates and customers safe. Job offers are contingent upon the results of background, drug screening, and reference check. Only after successfully passing these pre-hire clearances are individuals approved for hire and ready to start their successful and rewarding career.

#CABO