Consulting Principal Lead Platform (Cloud, Data & AI)

Who are we

Amdocs helps those who build the future to make it amazing. With our market-leading portfolio of software products and services we unlock our customers innovative potential empowering them to provide next-generation communication and media experiences for both the individual end user and enterprise customers. Our employees around the globe are here to accelerate service providers migration to the cloud enable them to differentiate in the 5G era and digitalize and automate their operations. Listed on the NASDAQ Global Select Market Amdocs had revenue of $5.00 billion in fiscal 2024. For more information visit

At Amdocs our mission is to empower our employees to Live Amazing Do Amazing every day. We believe in creating a workplace where you not only excel professionally but also thrive personally. Through our culture of making a real impact fostering growth embracing flexibility and building connections we enable them to live meaningful lives while making a difference in the world.

In one sentence

As the Platform (Cloud Data & AI) Practice Lead you will architect deliver and scale enterprise-grade cloud data engineering and AI/ML platforms. You will define and implement frameworks reusable assets and best practices that enable teams to deliver secure scalable and innovative solutions across AWS Azure GCP Snowflake Databricks and leading AI/ML platforms. Your leadership will ensure seamless integration of cloud infrastructure modern data engineering and advanced analytics to accelerate business value.

What will your job look like

Key Responsibilities

• Strategic Leadership: Define and execute the integrated platform strategy and roadmap for cloud data and AI aligned with business and technology goals.
• Cloud Platform Engineering: Architect and oversee the deployment of secure scalable and cost-optimized cloud platforms (AWS Azure GCP) including IaaS PaaS container orchestration (Kubernetes OpenShift) and automation (Terraform ARM CloudFormation).
• Data Engineering: Lead the design and implementation of cloud-native data platforms including data lakes lakehouses streaming and batch pipelines using tools like Databricks Snowflake Apache Spark Kafka Airflow DBT and cloud-native services.
• AI/ML Platform Enablement: Build and operationalize AI/ML platforms (Azure ML AWS SageMaker GCP Vertex AI Databricks ML) supporting model development deployment monitoring and MLOps.
• Reusable Assets & IP: Develop and maintain reusable tools accelerators frameworks and IP for platform engineering data migration AI/ML integration and automation.
• AI-Embedded Solutions: Embed AI/ML capabilities into platform offerings enabling advanced analytics intelligent automation and data-driven decision-making.
• DataOps & MLOps: Champion DataOps and MLOps practices (CI/CD automated testing monitoring observability lineage) for data and AI workloads.
• Monitoring & Observability: Implement and manage platform observability using Prometheus Grafana ELK/EFK Stack Datadog CloudWatch Azure Monitor Google Cloud Operations Suite OpenTelemetry Great Expectations Monte Carlo and OpenLineage.
• Executive & Customer Engagement: Present technical solutions and transformation roadmaps to executives and customers; deliver technical briefings workshops and thought leadership.
• RFPs Proposals & SOWs: Actively participate in RFP responses proposal development and SOW creation for platform transformation opportunities.
• Collaboration: Work closely with application analytics and security teams to deliver integrated end-to-end solutions.
• Mentorship: Lead and mentor cross-functional teams fostering a culture of innovation continuous improvement and professional growth.

All you need is...

Key Responsibilities

• Strategic Leadership: Define and execute the integrated platform strategy and roadmap for cloud data and AI aligned with business and technology goals.
• Cloud Platform Engineering: Architect and oversee the deployment of secure scalable and cost-optimized cloud platforms (AWS Azure GCP) including IaaS PaaS container orchestration (Kubernetes OpenShift) and automation (Terraform ARM CloudFormation).
• Data Engineering: Lead the design and implementation of cloud-native data platforms including data lakes lakehouses streaming and batch pipelines using tools like Databricks Snowflake Apache Spark Kafka Airflow DBT and cloud-native services.
• AI/ML Platform Enablement: Build and operationalize AI/ML platforms (Azure ML AWS SageMaker GCP Vertex AI Databricks ML) supporting model development deployment monitoring and MLOps.
• Reusable Assets & IP: Develop and maintain reusable tools accelerators frameworks and IP for platform engineering data migration AI/ML integration and automation.
• AI-Embedded Solutions: Embed AI/ML capabilities into platform offerings enabling advanced analytics intelligent automation and data-driven decision-making.
• DataOps & MLOps: Champion DataOps and MLOps practices (CI/CD automated testing monitoring observability lineage) for data and AI workloads.
• Monitoring & Observability: Implement and manage platform observability using Prometheus Grafana ELK/EFK Stack Datadog CloudWatch Azure Monitor Google Cloud Operations Suite OpenTelemetry Great Expectations Monte Carlo and OpenLineage.
• Executive & Customer Engagement: Present technical solutions and transformation roadmaps to executives and customers; deliver technical briefings workshops and thought leadership.
• RFPs Proposals & SOWs: Actively participate in RFP responses proposal development and SOW creation for platform transformation opportunities.
• Collaboration: Work closely with application analytics and security teams to deliver integrated end-to-end solutions.
• Mentorship: Lead and mentor cross-functional teams fostering a culture of innovation continuous improvement and professional growth.

Technical Skills Required

• 12 years in platform engineering cloud data or AI roles with deep expertise in AWS Azure GCP Snowflake Databricks and leading AI/ML platforms.
• Proven experience architecting and migrating enterprise platforms (applications data AI/ML) to cloud.
• Mastery of cloud-native engineering (Kubernetes Docker Terraform) data engineering (Spark Kafka Airflow DBT) and AI/ML platforms (Azure ML SageMaker Vertex AI Databricks ML).
• Strong programming skills (Python SQL Spark Java) and experience with cloud-native services and automation
• Demonstrated experience with DataOps and MLOps: CI/CD data quality lineage and observability tools.
• Hands-on experience embedding AI/ML into platforms and enabling advanced analytics.
• Data security IAM encryption and regulatory compliance expertise.
• Leadership and consulting experience with strong communication and executive presentation skills.

Nice-to-Have

Certifications in AWS Azure GCP Snowflake Databricks or leading AI/ML platforms.

Experience with open-source platform data or AI engineering tools.

Background in app modernization MLOps or cloud security.

Why you will love this job:

• You will be challenged to strategize direct and build a high performance organization; have the opportunity to use your forward-thinking and critical thinking to carry out regional responsibility or global responsibility based on your job; coordinate driving penetration into the existing and new opportunities and accounts to grow the overall business.
• We offer a wide range of stellar benefits including health dental vision and life insurance as well as paid time off sick time and parental leave!

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race religion color national origin sex gender gender expression sexual orientation age marital status veteran status or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process to perform essential job functions and to receive other benefits and privileges of employment. Please contact us to request accommodation.