Principal Engineer – AI and Data Science

Description

• Evaluates technology to drive features and roadmaps. Maps technology trends to internal vision.
• Maintains excitement for a process and drives to new directions of meeting the goal even when odds and setbacks render one path impassable.
• Pre-emptively sees downstream consequences and effectively tailors influencing strategy to support a positive outcome. Uses experts or other third parties to influence.
• Work on developing next generation AI technologies such as Text Mining, Machine Learning, Deep Learning to improve product capabilities and development processes.
• Identifies how the cost of change weighs against the benefits and advises accordingly.
• Proactively identifies and removes project obstacles or barriers on behalf of the team.
• Provide guidance to developers with either planning and execution and/or design architecture using agile methodologies such as SCRUM.
• Balances value propositions for competing stakeholders. Recommends a well-researched recommendation of buy vs. build solution.
• Capture system level requirements by brainstorming with CTO, Sr. Architects, Data Scientists, Businesses & Product Managers
• 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.
• Work with Product Line Leaders (PLLs) to understand product requirements & develop a strategy and vision.
• 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.
• Influences through others; builds direct and "behind the scenes" support for ideas.
• 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.
• 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.
• Leads impact assessment and decision related to technology choices, design /architectural considerations, and implementation strategy.

Requirements

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

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance