Principal AI Systems Architect

Technology, Data & Digital · Data, AI & Analytics · Artificial Intelligence · Data Engineering · Software Engineering

In short

Principal AI Systems Architect needed to guide AI design and use in Core Networks delivery across the Americas, focusing on shared platforms and customer data. This hands-on role requires production AI shipping experience, building and deploying AI agents, data pipelines, and reusable solutions, and ensuring they move from pilot to production.

Responsibilities

Build and deploy AI agents, data pipelines, and reusable solutions alongside engineering and field teams.
Guide the technical work of small squads.
Take agents from pilot to production by developing evaluation methods, improving reliability, defining monitoring and operating procedures, and supporting handover.
Decide which delivery steps should use AI, be redesigned, or remain unchanged, and select suitable approaches from available platforms.
Define what should be shared across teams and what should be specific to a domain.
Set quality and production-readiness expectations.
Establish data and knowledge requirements, including sources and formats, and define customer data controls for access, location, retention, and masking.
Work with customer and Core Networks specialists to ensure solutions reflect network operations and connect effectively with customer systems.
Set safeguards for automated actions, including policy controls, human review where needed, and rollback procedures.
Maintain a record of technical decisions.
Raise risks, dependencies, and platform needs early, with recommendations for addressing them.

Requirements

Hands-on experience building, deploying, and operating production AI systems, such as applications using large language models, AI agents, or retrieval-augmented generation.
Experience includes evaluation, monitoring, reliability, security, and data governance.
Ability to write and review code, with experience in Python, AI agent and workflow tools, and enterprise cloud environments.
Working knowledge of Kubernetes, GitOps, continuous integration and delivery, and cloud-based network functions.
Knowledge of customer data controls, including access, data location, retention, masking, and governance.
Experience delivering in large enterprise IT environments with multiple teams, evolving platforms, and layered governance.
Ability to assess complex systems, make evidence-based decisions, and explain technical choices in business terms and business needs in practical terms.
Ability to collaborate constructively with distributed teams and build shared accountability.

Desired Qualifications

Experience in telecommunications, network automation, service reliability, customer operations platforms, Microsoft technologies, or multi-team AI development is an asset.
Readiness to learn, adapt, and develop the skills needed to thrive in an AI-enabled future.

Benefits

Outstanding opportunity to use skills and imagination to push the boundaries of what’s possible.
Challenging work in a team of diverse innovators.
Competitive package to help with individual needs and goals.
Excellent health benefits including choice of three medical plan options and a dental plan option.
Company credits equal to the cost Ericsson pays toward medical and dental premiums.
Invest in both short and long-term financial wellbeing.
Ericsson US 401(k) Plan with automatic 3% company contribution and a 100% match up to 4% of eligible pay.
Company credits equal to the cost of basic life insurance, accidental death and dismemberment coverage, and short-term and long-term disability coverage.
Option to participate in Ericsson’s Stock Purchase Plan.
15 days of accrued vacation, up to 3 personal days per year, 11 annual holidays.
8 hours of volunteer time and 80 hours of sick time annually.
Up to 16 weeks of paid maternity leave.
6 weeks of parental or adoption leave at 100% of pay.
Financial wellness programs, educational assistance, matching gifts, and recognition programs.

Skills

PythonKubernetesGitOpsCI/CDLarge Language ModelsAI AgentsRetrieval Augmented Generation

#AI#Systems Architecture#Core Networks#Delivery#Cloud#Production AI

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