AI Solutions Architect

We’re seeking a highly skilled and hands‑on AI Solution Architect to join our team and help drive the development of a cutting‑edge AIOps platform. This individual will play a pivotal role in designing and implementing AI‑driven solutions that transform IT Operations—enhancing automation, observability, and incident response across complex enterprise environments. As a key member of our architecture team, you will collaborate with data scientists, engineers, and IT stakeholders to architect AI‑driven solutions that proactively detect, diagnose, and resolve operational issues across complex infrastructure and application landscapes.

We are seeking someone who enjoys building real world systems in production environments.

• Architect and lead the development of an enterprise‑grade AIOps platform leveraging machine learning, deep learning, and advanced analytics.
• Design scalable AI pipelines for anomaly detection, predictive analytics, root cause analysis, and intelligent alerting.
• Collaborate cross‑functionally with engineering, Dev Ops, and IT teams to integrate AI capabilities into existing operational workflows and tools.
• Evaluate and select appropriate technologies, frameworks, and cloud‑native services in Azure and GCP to support real‑time data ingestion, processing, and model deployment.
• Ensure platform reliability and performance, with a focus on scalability, security, and maintainability.
• Mentor and guide engineering teams on best practices in AI architecture and model lifecycle management.
• Stay current with emerging trends in AIOps, MLOps, and IT automation to continuously evolve the platform.

• Bachelor’s or master’s degree in computer science, Data Science, Machine Learning, or related field
• Experience as a Solution Architect or AI/ML Architect in enterprise environments.
• 3+ years of hands‑on experience building AIOps platforms and solutions in IT environments.
• Experience in IT Operations, infrastructure monitoring, incident management, and observability tools.
• Experience with AI/ML frameworks (e.g., Tensor Flow, PyTorch, Scikit‑learn) and data engineering tools (e.g., Spark, Kafka, Airflow) and knowledge graphs.
• Experience in Python and familiar with key AI/ML libraries (e.g., Tensor Flow, PyTorch, Hugging Face).
• Experience with cloud platforms such as Azure and Google Cloud Platform (GCP), including their native Data and AI/ML toolsets and services like ADLS, Azure Machine Learning, Azure Foundry, GCS and GCP Vertex AI. Experience with container orchestration technologies like Kubernetes, and hands‑on expertise in working with Large Language Models (LLMs) and Generative AI tools.

• Experience with log and metrics analysis, time‑series forecasting, and NLP for IT ticket classification.
• Knowledge of MLOps practices for model deployment, monitoring, and governance.
• Exposure to tools like Service Now, Datadog, Prometheus, Grafana, ELK Stack, etc.
• Certified in AI engineering in Azure and GCP.

Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at  where you can also request a call. Please note should your inquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.