Software Engineer (Backend) at Latent AI

San Francisco, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Healthcare, AIIndustries

Requirements

Highly proficient with command line and keyboard shortcuts
Holds self and others to high standards
Thrives in a high-energy team environment
Eager to master new technologies and clinical domains
Strong focus on automation to increase leverage
Takes ownership and solves problems proactively
Excels at defining standards and building simple abstractions to manage complexity
Significant experience building various types of systems and solutions
Primary language: TypeScript
Deep familiarity with distributed systems technologies such as Redis, PostgreSQL, Temporal, and Kafka
Experience architecting distributed systems and managing complexity in high-stakes environments
Bonus: Strong Kubernetes experience and ability to work on Helm charts

Responsibilities

Design and build robust data pipelines and architect distributed systems to handle high-volume clinical data
Build and maintain core functionality for seamless, reliable integration with disparate health systems and Electronic Health Records (EHRs)
Integrate with and manage complexity from in-house clinical AI models and external off-the-shelf models
Architect and implement complex business logic essential to workflows like Prior Authorizations and Patient Interactions

Skills

Key technologies and capabilities for this role

Data PipelinesDistributed SystemsEHR IntegrationAI IntegrationBackend DevelopmentCommand LineAutomationBusiness Logic

Questions & Answers

Common questions about this position

What is the salary range for this Backend Engineer position?

The pay scale for this role ranges from $165,000 to $250,000.

Is this Backend Engineer role remote or onsite?

This is a fully onsite position requiring 5 days in-office in San Francisco, CA.

What technical skills are required for this Backend Engineer role?

Required skills include proficiency in TypeScript as the primary language, deep familiarity with distributed systems technologies such as Redis, PostgreSQL, Temporal, and Kafka, and experience architecting distributed systems.

What kind of company culture does Latent AI have for engineers?

The team values builders who are proficient with tools, hold high standards, love high-energy environments, take ownership, automate tasks, and excel at managing complexity through standards and abstractions.

What makes a strong candidate for this Backend Engineer position?

Strong candidates have significant experience building various systems, speak command line fluently, embrace automation and ownership, manage complexity well, and have expertise in TypeScript and distributed systems like Redis, PostgreSQL, Temporal, Kafka; Kubernetes experience is a bonus.

Latent AI

Optimizes AI for edge computing applications

About Latent AI

Latent AI focuses on enhancing artificial intelligence for edge computing, which involves processing data close to where it is generated, like on smartphones and IoT devices. Their main product is an edge MLOps workflow that automates and simplifies the deployment of AI models on these devices, ensuring they are efficient, secure, and require minimal maintenance. This company stands out from competitors by specifically targeting the edge computing market and providing a software development kit (SDK) called Latent LEIP, which aids developers in creating and deploying AI models. The goal of Latent AI is to make AI more accessible and efficient for applications that need real-time data processing, such as in autonomous vehicles and smart cities.

Menlo Park, CaliforniaHeadquarters

2018Year Founded

$21.9MTotal Funding

SERIES_ACompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine LearningIndustries

51-200Employees

Risks

Competition from tech giants like Google and Amazon threatens Latent AI's market share.

Rapid AI advancements may outpace Latent AI's current capabilities, requiring continuous innovation.

Dependency on key partnerships, like Booz Allen, poses risks if relationships change.

Differentiation

Latent AI specializes in optimizing AI for edge computing applications.

Their edge MLOps workflow ensures efficient, secure AI model deployment on edge devices.

Latent AI's SDK, Latent LEIP, streamlines AI model creation and deployment for developers.

Upsides

Growing interest in federated learning enhances privacy and efficiency for edge AI.

The rise of TinyML aligns with Latent AI's focus on resource-constrained edge devices.

5G technology adoption boosts data transmission speed for Latent AI's solutions.

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