Staff Software Engineer, Backend (Infrastructure)

Otter.ai•Seattle, WA

18h•Hybrid

About The Position

We are seeking a talented Staff Software Engineer, Backend (Infrastructure) to lead the development, deployment, and management of web services and infrastructure that empower AI-driven products and initiatives. As part of our dynamic engineering team, you'll collaborate closely with AI researchers, product managers, and technologists to deliver innovative solutions that transform the experiences of end-user professionals and enterprise clients across diverse industries. You will define and drive the architecture of scalable solutions utilizing technologies like MySQL, Vitess, Kafka, Cassandra, Redis, and big data platforms. You will leverage your deep expertise in Python to build and enhance backend systems that seamlessly integrate with machine learning and AI models, while establishing engineering best practices for the broader team. You will design and implement robust business logic using web frameworks such as Django, ensuring compatibility with AI components and integration with databases. You will write reusable, efficient, and maintainable code that underpins our high-performance web services and supports real-time AI analytics. You will partner with AI teams to streamline data pipelines, optimize model deployment, and ensure backend systems effectively support AI-based product features. You will serve as a key technical voice with stakeholders across the organization, translating complex infrastructure strategies into clear direction and influencing roadmaps related to AI-enabled infrastructure.

Requirements

Holds a Bachelor's, Master's, or Ph.D. in Computer Science or a related field.
Demonstrates strong expertise in databases, distributed systems, backend performance optimization, and familiarity with backend requirements for machine learning infrastructure.
Demonstrates a solid understanding of database internals, transactions, indexing, and experience in schema design optimized for AI data workloads.
10+ years of experience in developing and architecting large-scale web services, preferably with exposure to supporting AI systems.
Possesses expert proficiency in Python or other programming languages such as Go, Java, or C++.
Has extensive experience with web frameworks like Django and is comfortable integrating systems with technologies such as MySQL, Redis, Elasticsearch, Kafka, and Cassandra, particularly in support of AI workflows.
Has hands-on experience deploying and managing services on AWS, particularly those interfacing with machine learning platforms.
Is driven by ownership and passionate about delivering impactful solutions from conception to deployment, especially in collaborative environments with AI-focused teams.
Brings substantial production server experience or equivalent backend expertise to the table.
Has excellent communication skills, a genuine curiosity for technology, and meticulous attention to detail.

Nice To Haves

Familiarity with HTTP, networking principles, and API design patterns beneficial to AI integrations.
Experience with operating systems, particularly Linux, and an understanding of their interactions with AI applications and services.

Responsibilities

Define and drive the architecture of scalable solutions utilizing technologies like MySQL, Vitess, Kafka, Cassandra, Redis, and big data platforms — shaping foundational systems that support sophisticated AI applications and workflows across the organization.
Leverage your deep expertise in Python to build and enhance backend systems that seamlessly integrate with machine learning and AI models, while establishing engineering best practices for the broader team.
Design and implement robust business logic using web frameworks such as Django, ensuring compatibility with AI components and integration with databases — and influence how these patterns are adopted at scale.
Write reusable, efficient, and maintainable code that underpins our high-performance web services and supports real-time AI analytics, setting the bar for code quality across teams.
Partner with AI teams to streamline data pipelines, optimize model deployment, and ensure backend systems effectively support AI-based product features — often driving alignment across multiple teams simultaneously.
Serve as a key technical voice with stakeholders across the organization, translating complex infrastructure strategies into clear direction and influencing roadmaps related to AI-enabled infrastructure.