Infrastructure Engineer

The individual in this role is accountable for infrastructure data, context, and knowledge-related designs within one or more network and service domains that enable AI and deterministic automation outcomes in accordance with architectural governance, standards, and policies.

This role facilitates delivery of technical context and data improvements by leading other infrastructure engineers and domain contributors in identifying source issues, defining remediation activities, and developing the templates, playbooks, documentation patterns, and supporting automation needed to improve trusted data and knowledge at source.

Within the Data Knowledge pillar, this individual provides hands‑on technical and network product expertise to help ensure configurations, telemetry, standards, policies, documentation, and operational knowledge are accurate, usable, and structured appropriately for downstream AI model consumption and deterministic automation use.

This individual will demonstrate a high level of technical expertise across network products, service implementations, and operational context, while also demonstrating the ability to decompose issues or objectives into units of work that can be assigned to other team members.

They advocate and advance more efficient solution delivery practices and evangelize strong design, engineering, and organizational practices that improve the trustworthiness and operational usefulness of context provided to AI and automation solutions.

• Confirm that business and technical context requirements are translated into actionable remediation plans, documentation patterns, templates, playbooks, and supporting guidance aligned to enterprise standards and policies.
• Lead technical efforts to identify and address data defects, documentation gaps, metadata issues, and operational knowledge weaknesses at source across network and service domains.
• Provide network product and service subject matter expertise to help data engineers and related teams define context assets suitable for AI model consumption and deterministic automation use.
• Guide the development of reusable templates, reference models, documentation structures, and technical knowledge patterns that improve context quality, consistency, and reuse.
• Mentor infrastructure resources on methods for improving source data quality, capturing operational knowledge, and documenting technical context in a way that supports trusted downstream consumption.
• Assist and mentor engineers by ensuring technical context artifacts and supporting data improvements comply with enterprise design, engineering, and governance expectations.
• Contribute to the creation and selection of functional and non‑functional requirements for context, documentation, and data quality improvements within and across domains.
• Review and guide approaches for correcting recurring source defects through preventative and detective quality measures that improve long‑term trust in AI‑relevant data and knowledge.
• Work with product and service subject matter experts to capture and clarify operational workflows, product behaviors, known constraints, and domain‑specific knowledge needed for downstream use.

• Strong experience working with network products, infrastructure services, and operational implementations in a complex enterprise environment.
• Advanced technical understanding of network service behavior, configurations, telemetry, dependencies, and operational workflows required to interpret and improve source data and knowledge.
• Experience identifying and helping remediate data defects, metadata issues, or documentation quality gaps at source within infrastructure or service domains.
• Ability to partner effectively with data engineers and related teams to translate technical infrastructure knowledge into usable structured and unstructured context assets for AI and automation consumption.
• Strong knowledge of how documentation, standards, policies, configurations, runbooks, and operational records contribute to trusted context for AI models and deterministic automation.
• Experience creating or guiding templates, playbooks, reference artifacts, and…