Data and AI Architect
- Responsible for identifying and evaluating the latest Artificial Intelligence (AI) capabilities, Large Language Models (LLMs) and technologies
- Responsible for integrating AI Models with applications using Model Context Protocol (MCP) and other cutting-edge capabilities to drive business results and innovation to propel organization's Data and Digital strategies
- Accountable for defining end-to-end AI solution architecture that integrates with the established data foundation to deliver insights and predictions
- Responsible for establishing strategies, design patterns, guardrails, decision matrices, information models and frameworks that drive operational efficiencies across the AI landscape
- Responsible for identifying gaps and opportunities in the AI landscape and formulate a roadmap for enhancements
- Responsible for assessing the latest LLMs and enabling them for use cases
- Accountable for the operationalization of new AI capabilities, LLMs and tools and ensuring seamless integration with existing systems and processes (e.g. security, scalability, performance, reliability, FinOps, recovery etc.)
- Collaborate with Responsible AI committee to establish Responsible AI and AI-Ops (LLM-Ops) practices across the organization ensuring industry standard best practices are incorporated and adhered to
- Responsible for providing technical leadership and mentorship to development teams on implementing AI technologies and patterns
- Responsible for defining and operationalizing AI optimization techniques to address performance, cost and efficiency
- Responsible for creating enterprise blueprints that tie together our business processes and workflows with data in a cohesive way that strengthens our overall AI capabilities, accelerates delivery, and promotes innovation across the Data & AI landscape
- Responsible for cultivating relationships with peer Data Management groups and Enterprise Architects to ensure alignment, compliance and long-term sustainability of our digital assets
- Consulting and/or participation in risk review process and Architecture Review board to ensure AI projects/tools/models align with the organization's risk management and architecture standards
- Ensure consistency of AI models & tools, and architectural best practices across the organization, driving adoption across our teams and systems
- Proactively identify opportunities for automation and continuous improvements
- Stay current with the latest trends, technologies, and best practices in the AI stack - management, governance, and architecture
- Participate and support Agile quarterly planning for the team
- Establish AI capabilities to seamlessly complement the Data Lake, Data Warehouse, forming a unified and holistic platform to meet all data requirements
- Ensure consistency of AI models, tools, and architectural best practices across the organization, driving adoption across our teams and systems
- Responsible for establishing synergies and decision trees to map the right AI tools for the use cases
- Support other business groups (such as Asset & Operations Integrity, Construction, Damage Prevention, etc.) with a variety pipeline related activity
- Accountability & Integrity: Takes ownership of actions, follows through on commitments, and stands up for what is right
- Results Orientation: Delivers positive outcomes through realistic planning and goal setting
- Decision-Making: Builds effective solutions using available information and makes timely, ethical decisions
- Legally authorized to work in the United States
- Bachelor's degree or higher in Computer Science, Engineering, Geoscience, Information Technology, Information Systems, related field or foreign equivalent
- 7 or more years of experience in data architecture, and data management in an enterprise environment
- 1 or more years of experience with design and enablement of enterprise AI
- 1 or more years of experience with implementation of GenAI based solutions (Agentic workflows)
- 1 or more years of experience using the AI Assistants (like Microsoft copilot cowork, Anthropic claude code, Snowflake CoCo) for product/solution development
- Intermediate level of knowledge and experience designing and implementing solutions using MCP technologies
- 7 or more years of experience with Cloud Platforms on Data Science and Analytics
- 7 or more years of experience implementing and supporting complex Data Management initiatives e.g., Snowflake, ADLS, Databricks
- 5 or more years of experience with database platforms such as Snowflake or Teradata with demonstrated strength in SQL, data modeling, ETL development, and data warehousing
- 5 or more years of Energy industry experience
- Hands on experience and proficiency in Data Management tools - SQL, SDE, JSON, XML, scripting languages such as Python Big Data technology stack including NoSQL, Spark, Hive, Kafka, StreamSets, IICS, ADF etc
- Experience with Spark and any of the following programming languages: Python, Scala, Java etc
- Hands on experience designing and implementing data ingestion techniques for real-time and batch processes into cloud based platforms
- Delta Lake experience with query optimization
- Work across structured, semi-structured, and unstructured data, with strong technical experience in large distributed systems, data warehousing, data lake at scale
- Deep subject matter expertise and hands on experience in designing, scaling and implementing data lake platform
- Advanced level of knowledge of master data management, real-time streaming data and cloud technologies
- Advanced knowledge of well data lifecycle from exploration through to development, drilling and completion, production and eventual abandonment or relinquishment
- Advanced level of proficiency in DevOps , including Agile development process, containers, and source code control systems
- Intermediate level of knowledge of Data Management principles, processes and data lifecycle
- Understanding of Data Science and related technologies
- Ability to take ownership, engage, lead change, achieve results, adapt, problem solve, manage risk and drive tasks to completion
- Ability to lead initiatives, multi-disciplinary project teams, and influence stakeholder buy-in
- Participate in strategy and planning sessions and be recognized as a capable team member that delivers value
- Demonstrated ability to deal with ambiguity and maintain effective performance under stressful and uncertain conditions
- Excellent oral and written communication skills; proven ability to represent point of view and discuss technical information with the business users in business language
- Team player, and self-driven individual who can multi-task, work independently under minimal supervision and deliver on commitments
- Excellent analytical mind and proven problem-solving skills
- Demonstrated leadership skills, with ability to engage at all levels of the organization
- Confident in engaging all levels of the organization in communicating a data strategy
- Ability to influence others and drive change around data standards and best practices
- Taking Care of Your Health & Wellness : Medical, dental, vision, mental health support, and wellness programs.
- Supporting and Building Financial Security : Competitive base pay, annual performance bonuses, and retirement savings plans.
- Promoting Work-Life Balance : Paid time off, paid parental leave, and family support resources.
- Offering Career Development : Access to training, mentoring, and internal career mobility tools.
- Guiding Recognition & Inclusion : Peer-nominated awards, inclusive culture, and employee resource groups.
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