Full-Time

Engineering Manager-Runtime Team

Confirmed live in the last 24 hours

WebAI

WebAI

51-200 employees

Modular deep learning platform for enterprises

Cybersecurity
AI & Machine Learning

Mid, Senior

Austin, TX, USA

Category
Engineering Management
Software Development Management
Required Skills
Rust
Agile
Python
Apache Kafka
Java
Go
C/C++
Requirements
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent work experience.
  • 8+ years of experience in software engineering, with at least 3 years in a leadership or management role. Experience in backend, distributed systems, or platform teams is a plus.
  • Strong proficiency in backend technologies, with a preference for experience in Golang. Familiarity with Python, Rust, and messaging systems like MQTT, Kafka, or NATS is a plus.
  • Experience managing engineering teams, overseeing development pipelines, including CI/CD processes, and working within complex system architectures and custom deployment strategies.
  • You have a proven track record of fostering growth in an engineering organization, both in terms of individual contributors and the team’s ability to deliver high-quality, scalable solutions.
  • Proven experience in software engineering management, particularly in AI technologies.
  • Strong understanding of machine learning, neural networks, and data architecture.
  • Excellent leadership skills with a track record of managing high-performing engineering teams.
  • Experience with Agile methodologies and software development cycles.
  • Proficient in programming languages such as Python, Java, or C++.
  • Exceptional problem-solving abilities and strong analytical skills.
  • Excellent verbal and written communication skills.
Responsibilities
  • lead and mentor a team of engineers, helping them grow their skills while ensuring delivery of complex technical projects.
  • provide guidance on the design and implementation of systems for both local air-gapped environments and customer-distributed deployments.
  • work closely with technical leads and product teams to drive new features and deliver robust, backwards-compatible updates that impact all of WebAI’s customers and products.
  • collaborate with stakeholders to balance technical decisions with product and business goals.
  • contribute to the growth and scalability of WebAI by improving the engineering processes, fostering a culture of continuous learning, and making technical decisions accessible to non-technical stakeholders.
  • influence the company’s ability to deliver AI-powered products and services, and have ownership in shaping a critical area that impacts the company’s future.

WebAI provides a Deep Learning Platform (DLP) that is modular and secure, aimed at researchers, developers, and enterprises wanting to implement advanced AI solutions. The platform allows users to collect, train, and deploy neural networks with minimal computational resources, making it ideal for edge computing where internet access may be limited. Unlike many competitors, WebAI focuses on low data requirements and high accuracy, ensuring that clients can operate efficiently without needing extensive data sets. The platform features strong encryption for data security and is designed for easy integration with existing systems. WebAI's goal is to democratize access to advanced AI technologies, making them available to a wider range of industries, including healthcare, finance, and manufacturing.

Company Stage

Series A

Total Funding

$74.9M

Headquarters

Grand Rapids, Michigan

Founded

N/A

Growth & Insights
Headcount

6 month growth

22%

1 year growth

22%

2 year growth

22%
Simplify Jobs

Simplify's Take

What believers are saying

  • The recent $60 million Series A funding and $700 million valuation highlight strong investor confidence and provide resources for further innovation and market expansion.
  • The appointment of industry veterans to the board brings valuable expertise and strategic guidance, potentially accelerating WebAI's growth and influence in the AI sector.
  • WebAI's ability to enable powerful AI on local devices can significantly reduce computing costs and enhance operational efficiency for enterprises, making it an attractive option for cost-conscious businesses.

What critics are saying

  • The competitive AI landscape, with major players like Google and Microsoft, poses a challenge for WebAI to maintain its market position and continue attracting clients.
  • Reliance on subscription fees and additional services for revenue may limit scalability if clients seek more flexible pricing models.

What makes WebAI unique

  • WebAI's platform is designed for low computational resource environments, making it ideal for edge deployments where cloud connectivity is limited, unlike many competitors who rely heavily on cloud infrastructure.
  • The company's focus on secure AI solutions with state-of-the-art encryption and proprietary runtime stacks sets it apart in industries like healthcare and finance that require high data security.
  • WebAI's modular and autonomous AI tools allow clients to train and deploy neural networks with minimal data, reducing the need for extensive computational power and making AI more accessible.

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