Principal Engineer – AI and Data Science

Overview

Lead design and development of AI‑driven data fabric and next‑gen database for grid software.

Key Responsibilities

• technical leadership
• data fabric
• ai development
• technology evaluation
• impact assessment
• stakeholder alignment

Tasks

-Conveys the value proposition for the company by assessing financial risks and gains of decisions and return on investment (ROI). -Finds important patterns in seemingly unrelated information. -Evaluates technology to drive features and roadmaps. Maps technology trends to internal vision. -Influences through others; builds direct and "behind the scenes" support for ideas. -Leads impact assessment and decision related to technology choices, design /architectural considerations, and implementation strategy. -Proactively identifies and removes project obstacles or barriers on behalf of the team. -Work with Product Line Leaders (PLLs) to understand product requirements & develop a strategy and vision. -Facilitates and coaches software engineering team sessions on requirements estimation and alternative approaches to team sizing and estimation. Leads a community of practice around estimation to share best practices among teams. -Pre-emptively sees downstream consequences and effectively tailors influencing strategy to support a positive outcome. Uses experts or other third parties to influence. -Be responsible for providing technical leadership and defining, developing, and building our next generation data fabric system with focus on semantic modeling, data catalog development, data access and integration layers software in a fast paced and agile development environment. -Capture system level requirements by brainstorming with CTO, Sr. Architects, Data Scientists, Businesses & Product Managers -Work on developing next generation AI technologies such as Text Mining, Machine Learning, Deep Learning to improve product capabilities and development processes. -Provide guidance to developers with either planning and execution and/or design architecture using agile methodologies such as SCRUM. -Identifies how the cost of change weighs against the benefits and advises accordingly. -Balances value propositions for competing stakeholders. Recommends a well-researched recommendation of buy vs. build solution. -Maintains excitement for a process and drives to new directions of meeting the goal even when odds and setbacks render one path impassable. -Drive innovation in our database systems and drive next level of performance, correctness, durability, and scalability of our data systems by bringing in AI and next generation modeling technologies.

Requirements

• ai
• distributed systems
• semantic modeling
• c++
• master’s
• 18+ yrs

What You Bring

-Expert level skills in design, architecture, and development, with an ability to take a deep dive in the implementation aspects if the situation demands. -Innovates and integrates new processes and/or technology to significantly add value to GE. -Able to clearly articulate the business drivers relevant to a given initiative. -Subject matter expert in AI, data quality, data systems and related technologies with ability to adapt and improvise in various situations. Expert in navigating through ambiguity and prioritizing conflicting asks. -Deep knowledge in distributed systems with focus on key database concepts like concurrency control, consensus algorithms, indexing, replication, and serialization. -Expert in core areas of semantic modeling, data structures, knowledge graph technologies and can implement them using language of choice when necessary – as a value offering. -Enjoy working remotely as part of a fully distributed team -Working on data system across multiple operating systems/cloud environments is considered strong plus. -Master’s Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum 18 years of experience. -Differentiates buzzwords from value proposition. Embraces technology trends that drive excellence beyond traditional practices (e.g., Test automation in lieu of traditional QA practices). -Able to effectively direct and mentor others in critical thinking skills. -Able to navigate accountability in a matrixed organization. -Able to verbalize what is behind decisions and downstream implications. Continuously reflecting on success and failures to improve performance and decision-making. -Proactively engages with cross-functional teams to resolve issues and design solutions using critical thinking and analysis skills and best practices. -Must have experience building systems or components of AI system including semantic modeling, distributed data management software -Proactively learns new solutions and processes to address seemingly unanswerable problems. -Experience in working in industrial environments is a strong plus. -Advanced degrees such as PhD specially in AI, distributed computing or data systems is strong plus. -Understands when change is needed. Participates in technical strategy planning. -Deep knowledge in AI, data quality, data systems and knowledge in methods such as B+ trees, LSM trees, Lamport clocks, etc. -Communicates and demonstrates a shared sense of purpose. Learns from failure. -Manages the process of building and maintaining a successful alliance. Understands and successfully applies common analytical techniques, including ROI, SWOT, and Gap analyses. -Have experience building cross-platform distributed data management software -Is open to embracing a new language/stack/polyglot -Have deep mastery of at least one of: C#, C/C++, Java, Kotlin, Rust, Scala, or other systems/primary enterprise language that is used in data systems

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About Ge Vernova

-Traces roots back to Edison and Alstom, merging power, renewable, digital & financial wings. -Headquartered in Cambridge, MA, crafts large-scale gas turbines, SMRs, wind turbines, hydro and grid tech to fuel economies. -On the nuclear front, advancing small modular reactors (like BWRX‑300) in partnership with utilities and supporting semiconductor projects. -Wind prowess spans onshore, offshore and blade making—with key sites like Dogger Bank offshore and blade plants in Spain. -Electrification arm tackles grid stability: HVDC, transformers, storage, conversion, plus GridOS software powering smarter infrastructure. -Weaves finance and consulting through energy-infrastructure investments, funding solar farms to pipelines via GE Energy Financial Services.

Sector Specialisms