Lead Platform Engineer

RTX•US-CT-REMOTE, CT

1d•$157,200 - $298,800•Remote

About The Position

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.

Requirements

Typically requires a University Degree or equivalent experience and minimum 12 years prior relevant experience, or an Advanced Degree in a related field and minimum 10 years experience
5+ years of experience with data science and machine learning.
5+ years of experience with the Software Development Life Cycle and software application / product development, including Python and the Python scientific stack.

Nice To Haves

A flexible and patient mindset, interested in working on a variety of multi-disciplinary challenges with varying stakeholders, partners, domains, and toolsets.
Relevant experience with cloud computing platforms (AWS and/or Azure.)
Organizational skills for knowledge, documentation, and data management
SQL, Node, REST APIs, testing libraries.
Experience building products that use Large Language Models (LLMs) and LLM APIs.
Technical leadership experience, such as being the engineering lead for a program, product, or large project.
Experience as part of a multi-disciplinary team
Experience with cloud computing.

Responsibilities

Collaborate with technical leadership, product managers, program/project managers, and business stakeholders to support the team as we bring advanced data capabilities to RTX.
Be the system integrator for APIs, SDKs, and other automation activities: lead multi-disciplinary efforts to bring advanced AI/ML capabilities to RTX through production software and cloud engineering, including generative AI, AIOps, GenOps, MLOps, and ML-augmented engineering. This includes ensuring that capabilities are designed, implemented, maintained, observed, and supported from end-to-end.
Maintain both high level and low level views of technical systems, and coordinate with teams and subject matter experts from other disciplines to realize successful realization.
Design, write, test, and deploy production quality software capabilities that are maintainable, automated (CI/CD), scalable, observable, organized, and readable. Ensure best practices are maintained, including quality and CI/CD automation.
Advise technical support and building of user documentation
Mentor early and mid career team members, supporting their ascension to senior and lead roles.