Sr. Manager, Software Engineering - Data Engineering

At G-P, our mission is to break down barriers to global business, enabling opportunities for everyone, everywhere. With remote-first and diverse teams all around the world, our people are key to achieving this mission. That’s why we trust our Dream Team members with the flexibility and autonomy to do their best and most innovative work, encourage and support their personal growth and career development, and believe in recognition for a job well done.

Our industry-leading SaaS-based Global Employment Platform™ enables our customers to expand and grow into 180+ countries, creating more opportunities for global success – without requiring entity or subsidiary setup. The technical opportunities you’ll experience here have a positive impact on people and their work/life possibilities around the world. Beyond the power of our platform, we never forget that behind every hire is a human being. And that brings us to you.

If you have a passion for automation, are a deep innovator, and want to solve complex problems that lead to a world of positive results, consider G-P. Here, your knowledge and experience will be crucial to helping design and develop high-performing cloud-based software products using traditional Agile methodologies and modern frameworks.

Beyond a competitive compensation and benefits package, what we offer to all employees along the way is the clear and simple promise of Opportunity Made Possible. Come expand your skills in new ways and  Areas of Focus Include (but not limited to): - Developing AI Platform features and capabilities: This includes working with AI engineers and product managers to design and implement new features, as well as working to ensure that the features are effective. - Deploying and managing AI Platform instances: This includes working with cloud providers to deploy and manage AI Platform instances, as well as working with customers to ensure that they can use the platform effectively. - Providing support to users: This includes answering questions, providing training, and troubleshooting problems. - Manage and mentor AI Platform team experience the thrill of your best innovations becoming reality.

About the Team

The AI Platform team is a dynamic group that melds data engineering, cloud engineering, product development, and AI research. Our responsibilities encompass the design, implementation, scaling, and maintenance of AI models, features, and services. We also fortify the foundational layer of AI tools and infrastructure, frameworks, and inference libraries for the AI research teams. Moreover, we constantly collaborate with the AI Research, Data Engineering, and Cloud Engineering teams to enhance AI models, add features, streamline tools, and devise automation and applications.

Our team is instrumental in enabling businesses to embrace AI by delivering a robust, scalable AI platform. This empowers businesses to concentrate on their core functions without the hassle of managing the underlying AI technology.

About the Role

As the hands-on Engineering Manager of the AI platform, you will be responsible for architecting the AI platform as well as hands-on software development and deployment. In addition to leading the team, you will work closely with AI research lab to ensure that research POC's are seamlessly translated into production-grade applications. You will also be responsible for recruiting, mentoring, and providing resources to a high-performing AI Platform team. You will be directly involved in the personal and professional development of your team members

What you will do: 

• Developing AI Platform features and capabilities: This includes working with AI engineers and product managers to design and implement new features, as well as working to ensure that the features are effective.
• Deploying and managing AI Platform instances: This includes working with cloud providers to deploy and manage AI Platform instances, as well as working with customers to ensure that they can use the platform effectively.
• Providing support to users: This includes answering questions, providing training, and troubleshooting problems.
• Manage and mentor AI Platform team

What we are looking for?

• A minimum of eight years of hands-on experience in constructing and scaling platforms by employing AI/ML techniques for model building and integration into applications.
• At least three years of experience managing engineering teams and contributing to their growth and development.
• Profound knowledge of the data ecosystem (data engineering, data analytics, data mining, etc.).
• Competence in software development with proficiency in Python, including experience with Spark, distributed computing, etc.
• Experience in architecting complex AI/ML systems and platforms.
• Familiarity with cloud development principles and patterns, with an emphasis on loosely coupled architectures and microservices.
• Knowledge of ML Ops lifecycle and adding observability and monitoring to such systems.
• Proficient in employing AI, ML, and statistical analysis tools and techniques.
• Sharp analytical and problem-solving skills coupled with a knack for rapidly grasping systems.
• Ability to work independently (and as a team) and with influence to solve complex problems and deliver results
• Zeal for establishing and adhering to best practices. - Stellar communication and presentation skills.
• A deep-rooted passion for AI and its boundless potential to address real-world challenges.

This unique role combines hands-on technical leadership with managerial responsibilities. You will be at the forefront of AI platform development and nurturing a team that contributes to the AI revolution. Your impact will be manifold as you work on groundbreaking AI technologies while building and mentoring a world-class engineering team

Nice to haves:

• Vector Databases: Experience with vector databases such as Milvus, FAISS, or Pinecone, and understanding of their optimization and use cases for large-scale search and retrieval applications. 
•  Information Retrieval: Proficiency in advanced information retrieval techniques, including ranking algorithms, query expansion, and relevance feedback.
• Data Privacy and Ethics: Understanding of data privacy and ethical considerations in NLP and AI, including differential privacy and bias mitigation techniques.
• Low Latency Systems: Experience with serving real-time processing and analysis of textual data streams, and the ability to integrate NLP systems into real-time applications

#LI-Remote