Principal Engineer – AI and Data Science

Job Description SummaryYou will be part of the core team at GE Vernova Electrification Software (GEV ESW) Business that is using software to enable de-carbonized future of energy by designing, building and delivering software applications & services for next generation Grid Software that is used by 40% of the world’s power utilities today. This position is responsible for building our next generation database system, data access and integration layers to meet the intense data demands of next generation power grid software by developing data fabric and semantic data modeling technologies. You will be responsible for designing and implementing highly complex modules, critical components, or a whole application/product in its entirety that enable AI-Based Application that uses multiple distribution and transmission applications using data fabric. This position is both hands on role and will also need to shape the AI strategy for Grid Software business in area of semantic modeling, knowledge graphs, text mining and AI technologies. The position is responsible for driving the design and development efforts related to architecture, scalability, availability, and performance in alignment with the product/application roadmap for highly complex database systems for grid of the future technologies.

Job Description

Roles and Responsibilities

 

In this role, you will:

• 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.
• 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.
• Feel passionate about developing high performance distributed systems with focus on key database concepts like concurrency control, consensus algorithms, replication, serializability theory, and view maintenance
• 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.
• Work with Product Line Leaders (PLLs) to understand product requirements & develop a strategy and vision.
• Capture system level requirements by brainstorming with CTO, Sr. Architects, Data Scientists, Businesses & Product Managers
• Leads impact assessment and decision related to technology choices, design /architectural considerations, and implementation strategy.
• 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.
• Expert level skills in design, architecture, and development, with an ability to take a deep dive in the implementation aspects if the situation demands.
• 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.
   

Desired Characteristics

Technical Expertise:

• Deep knowledge in AI, data quality, data systems and knowledge in methods such as B+ trees, LSM trees, Lamport clocks, etc.
• Deep knowledge in distributed systems with focus on key database concepts like concurrency control, consensus algorithms, indexing, replication, and serialization.
• Have experience building cross-platform distributed data management software
• 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.
• Is open to embracing a new language/stack/polyglot
• Enjoy working remotely as part of a fully distributed team

 

Business Acumen:

• Evaluates technology to drive features and roadmaps. Maps technology trends to internal vision.
• Differentiates buzzwords from value proposition. Embraces technology trends that drive excellence beyond traditional practices (e.g., Test automation in lieu of traditional QA practices).
• Balances value propositions for competing stakeholders. Recommends a well-researched recommendation of buy vs. build solution.
• Conveys the value proposition for the company by assessing financial risks and gains of decisions and return on investment (ROI).
• Manages the process of building and maintaining a successful alliance. Understands and successfully applies common analytical techniques, including ROI, SWOT, and Gap analyses.
• Able to clearly articulate the business drivers relevant to a given initiative.

 

Leadership:

• Influences through others; builds direct and "behind the scenes" support for ideas.
• Pre-emptively sees downstream consequences and effectively tailors influencing strategy to support a positive outcome. Uses experts or other third parties to influence.
• Able to verbalize what is behind decisions and downstream implications. Continuously reflecting on success and failures to improve performance and decision-making.   
• Understands when change is needed. Participates in technical strategy planning.
• Proactively identifies and removes project obstacles or barriers on behalf of the team.
• Able to navigate accountability in a matrixed organization.
• Communicates and demonstrates a shared sense of purpose. Learns from failure.
   

Personal Attributes:

• Able to effectively direct and mentor others in critical thinking skills.
• Proactively engages with cross-functional teams to resolve issues and design solutions using critical thinking and analysis skills and best practices.
• Finds important patterns in seemingly unrelated information.
• Influences and energizes other toward the common vision and goal.
• Maintains excitement for a process and drives to new directions of meeting the goal even when odds and setbacks render one path impassable.
• Innovates and integrates new processes and/or technology to significantly add value to GE.
• Identifies how the cost of change weighs against the benefits and advises accordingly.
• Proactively learns new solutions and processes to address seemingly unanswerable problems.

Job Requirements

•  Master’s Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum 18 years of experience.
• Must have experience building systems or components of AI system including semantic modeling, distributed data management software
• 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

 

Desired Qualifications:

• Experience in working in industrial environments is a strong plus.
• Working on data system across multiple operating systems/cloud environments is considered strong plus.
• Advanced degrees such as PhD specially in AI, distributed computing or data systems is strong plus.

Additional Information