Drive enterprise-scale AI-first initiatives by combining strong analytical rigor with cross-functional leadership to deliver business impact. Lead strategy execution and adoption of data and AI capabilities across product engineering and business teams.
Key Responsibilities
Lead AI-first strategy and execution: Define and operationalize AI-centric use cases ensuring alignment with enterprise data and platform strategy.
Drive data-driven decision-making: Leverage advanced analytics to shape product direction prioritize investments and measure business outcomes.
Orchestrate cross-functional delivery: Align engineering data science product UX and business stakeholders to deliver integrated solutions at scale.
Translate business needs into AI solutions: Bridge strategy and execution by converting business problems into scalable data/AI solutions.
Own end-to-end program delivery: Establish operating models governance and execution frameworks to drive predictability and accountability.
Influence senior stakeholders: Communicate insights trade-offs and progress to executive leadership with clarity and impact.
Champion adoption and value realization: Ensure delivered solutions drive measurable business outcomes and enterprise adoption.
Continuously evolve capabilities: Stay current on emerging AI trends tools and frameworks to embed innovation into the platform roadmap.
Required Skills
Analytical Excellence
Strong problem-solving and structured thinking
Experience with data modeling metrics definition and performance analysis
Ability to synthesize complex data into actionable insights
AI & Data Orientation (AI-first mindset)
Deep understanding of AI/ML concepts data platforms and agentic systems
Experience translating business use cases into AI-driven solutions
Familiarity with modern AI stacks data fabrics and automation frameworks
Cross-functional Leadership
Proven ability to lead across product engineering data UX and business functions
Strong stakeholder management and influencing skills without direct authority
Experience driving alignment across global and matrixed organizations
Execution & Program Management
Expertise in operating models prioritization frameworks and governance
Ability to manage complex multi-stream programs with clear ownership and outcomes
Communication & Storytelling
Executive-level communication with a focus on clarity outcomes and decision enablement
Qualifications
Bachelors or Masters degree in Engineering Computer Science Data Science or related field
Proven years of experience in program management product management or data/AI leadership roles
Demonstrated experience leading enterprise-scale AI/Data initiatives
Proven track record of delivering cross-functional programs with measurable business impact
Experience working in global matrixed environments with senior stakeholder engagement
Required Skills:
Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. Understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understands the concept of region and AZs. Provide L2 support production systems like application database middleware components infrastructure and network components. Manage production incidents end-to-end within defined SLAs with focus on resolution rather than who caused it. Interact with various stakeholders such as Release managers program leads service managers development and test leads Review operational readiness requirements such as monitoring and alerting log rotation and resilience of the components and report the gaps Provide pre-implementation support with activities such as release notes review and implementation dry runs. Protect production components by running health checks monitoring latency and memory utilization. Automate day-to-day activities and propose changes that improve reliability Participate in CAB and provide feedback on change requests Support the DevOps team in testing the promoted pipelines and suggest automation of configuration items. Practice incident management best practices and perform RCA. Participate in disaster recovery tests and operational acceptance tests Analyze the technology stack that makes up the product and optimize recovery time objective. Work with team members spread across and time zones Share knowledge document improvements and mentor junior resources It is good to have skills using Jenkins to orchestrate builds and link to Sonar Maven etc. to build out the CI/CD pipeline. Support deployments of code into multiple lower environments. Supporting current processes needed with an emphasis on automating everything as soon as possible. It is good to have skill to design Implement and enhance our deployment automation based on Chef. We need proven experience designing and implementing an overall release and deployment process. It is good to have skill to design and implement a Git based code management strategy that will support multiple environment deployments in parallel. Experience with automation for Branch management code promotions and version management. Engage in and improve the whole lifecycle of servicesfrom inception and design through deployment operation and refinement. Requirements MQ/EB Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. An understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understand the concept of region and AZs. Deployments MTF/Prod Maintenance items (including stop/start Disaster Recovery-related activities etc.) CR for changes in MTF/Prod Good knowledge on Nginx Tools - Log Monitoring Tool - Splunk Application Monitoring tool - Dynatrace Ticketing incident/problem management tool - Remedy Dev-ops Basics - CI-CD Basics Overview of Git Bit-bucket SonarQube Ansible/Chef Skills - Linux & Shell Scripting ITIL / ITSM PL/SQL Troubleshooting Jenkins - CI/CD Groovy Scripting/Yaml Ansible/Chef Nginx Java / JEE Event-Driven Architectures MQ or NATS broker or similar messaging solutions. Kafka Client-server communication aspects - sockets TLS protocol Understand the concept of region and AZs.
Role OverviewDrive enterprise-scale AI-first initiatives by combining strong analytical rigor with cross-functional leadership to deliver business impact. Lead strategy execution and adoption of data and AI capabilities across product engineering and business teams. Key ResponsibilitiesLead AI-first...
Role Overview
Drive enterprise-scale AI-first initiatives by combining strong analytical rigor with cross-functional leadership to deliver business impact. Lead strategy execution and adoption of data and AI capabilities across product engineering and business teams.
Key Responsibilities
Lead AI-first strategy and execution: Define and operationalize AI-centric use cases ensuring alignment with enterprise data and platform strategy.
Drive data-driven decision-making: Leverage advanced analytics to shape product direction prioritize investments and measure business outcomes.
Orchestrate cross-functional delivery: Align engineering data science product UX and business stakeholders to deliver integrated solutions at scale.
Translate business needs into AI solutions: Bridge strategy and execution by converting business problems into scalable data/AI solutions.
Own end-to-end program delivery: Establish operating models governance and execution frameworks to drive predictability and accountability.
Influence senior stakeholders: Communicate insights trade-offs and progress to executive leadership with clarity and impact.
Champion adoption and value realization: Ensure delivered solutions drive measurable business outcomes and enterprise adoption.
Continuously evolve capabilities: Stay current on emerging AI trends tools and frameworks to embed innovation into the platform roadmap.
Required Skills
Analytical Excellence
Strong problem-solving and structured thinking
Experience with data modeling metrics definition and performance analysis
Ability to synthesize complex data into actionable insights
AI & Data Orientation (AI-first mindset)
Deep understanding of AI/ML concepts data platforms and agentic systems
Experience translating business use cases into AI-driven solutions
Familiarity with modern AI stacks data fabrics and automation frameworks
Cross-functional Leadership
Proven ability to lead across product engineering data UX and business functions
Strong stakeholder management and influencing skills without direct authority
Experience driving alignment across global and matrixed organizations
Execution & Program Management
Expertise in operating models prioritization frameworks and governance
Ability to manage complex multi-stream programs with clear ownership and outcomes
Communication & Storytelling
Executive-level communication with a focus on clarity outcomes and decision enablement
Qualifications
Bachelors or Masters degree in Engineering Computer Science Data Science or related field
Proven years of experience in program management product management or data/AI leadership roles
Demonstrated experience leading enterprise-scale AI/Data initiatives
Proven track record of delivering cross-functional programs with measurable business impact
Experience working in global matrixed environments with senior stakeholder engagement
Required Skills:
Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. Understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understands the concept of region and AZs. Provide L2 support production systems like application database middleware components infrastructure and network components. Manage production incidents end-to-end within defined SLAs with focus on resolution rather than who caused it. Interact with various stakeholders such as Release managers program leads service managers development and test leads Review operational readiness requirements such as monitoring and alerting log rotation and resilience of the components and report the gaps Provide pre-implementation support with activities such as release notes review and implementation dry runs. Protect production components by running health checks monitoring latency and memory utilization. Automate day-to-day activities and propose changes that improve reliability Participate in CAB and provide feedback on change requests Support the DevOps team in testing the promoted pipelines and suggest automation of configuration items. Practice incident management best practices and perform RCA. Participate in disaster recovery tests and operational acceptance tests Analyze the technology stack that makes up the product and optimize recovery time objective. Work with team members spread across and time zones Share knowledge document improvements and mentor junior resources It is good to have skills using Jenkins to orchestrate builds and link to Sonar Maven etc. to build out the CI/CD pipeline. Support deployments of code into multiple lower environments. Supporting current processes needed with an emphasis on automating everything as soon as possible. It is good to have skill to design Implement and enhance our deployment automation based on Chef. We need proven experience designing and implementing an overall release and deployment process. It is good to have skill to design and implement a Git based code management strategy that will support multiple environment deployments in parallel. Experience with automation for Branch management code promotions and version management. Engage in and improve the whole lifecycle of servicesfrom inception and design through deployment operation and refinement. Requirements MQ/EB Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. An understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understand the concept of region and AZs. Deployments MTF/Prod Maintenance items (including stop/start Disaster Recovery-related activities etc.) CR for changes in MTF/Prod Good knowledge on Nginx Tools - Log Monitoring Tool - Splunk Application Monitoring tool - Dynatrace Ticketing incident/problem management tool - Remedy Dev-ops Basics - CI-CD Basics Overview of Git Bit-bucket SonarQube Ansible/Chef Skills - Linux & Shell Scripting ITIL / ITSM PL/SQL Troubleshooting Jenkins - CI/CD Groovy Scripting/Yaml Ansible/Chef Nginx Java / JEE Event-Driven Architectures MQ or NATS broker or similar messaging solutions. Kafka Client-server communication aspects - sockets TLS protocol Understand the concept of region and AZs.