Trust In SODA
Do you want to play a defining role in a well backed AI company building the next generation of intelligent agents?
Location:
San Francisco or Boston Compensation:
$220k - $240k Employment Type:
Full time Model:
Hybrid (days on site, 3 days remote)
This company is building AI agents that automate complex, manual workflows across one of the largest and most operationally complex industries in the world. What started with voice, the hardest and highest impact interface, is rapidly expanding into full end-to-end workflow automation across sales, servicing, and claims. The long term vision is to create reasoning agents capable of operating autonomously across entire enterprise systems.
With over $70M raised, including a recent large Series B led by top tier venture firms, the company is entering a phase of rapid scale. Engineering is the core of the business, and technical decisions made today will define how intelligent systems operate in real production environments for years to come.
The Opportunity:
As a Staff Software Engineer, you will be a senior technical leader responsible for shaping foundational systems that power AI-driven products at scale. This role goes far beyond feature delivery. You will own architectural direction, influence platform strategy, and build systems that enable reliable, observable, high-performance AI agents in a regulated, mission-critical environment.
You will work with an elite group of engineers, researchers, and product leaders who value strong technical judgment, clear communication, and high ownership. This is a role for someone who thrives in ambiguity, enjoys solving hard infrastructure problems, and wants to see their work have immediate, real world impact.
What You Will Do:
Define and drive the technical vision for core platforms and domains, including architecture, infrastructure, tooling, and performance Design, build, and operate scalable backend systems that leverage foundational LLMs and asynchronous workflows Lead architectural decisions and trade-offs, balancing speed of iteration with long-term reliability and maintainability Partner closely with product, data science, and infrastructure teams to translate business strategy into durable technical roadmaps Serve as a technical mentor through design reviews, code reviews, and hands-on guidance, raising the bar for engineering excellence Own operational excellence across the stack, including debugging complex issues, participating in on-call, and leading post-mortems Define, measure, and improve reliability metrics such as SLAs, SLOs, and SLIs Identify technical debt and drive initiatives that improve system quality, performance, and developer velocity Introduce new technologies and processes that materially improve how teams build and ship software Represent the engineering organization externally when appropriate through technical talks, open source, or partner engagement
What Were Looking For:
8+ years of experience building and operating high-quality production software, with strong depth in Python Demonstrated experience architecting asynchronous, distributed, high-throughput systems in production Strong expertise with Python frameworks such as FastAPI, Django, and asyncio or equivalent Proficiency with Node.js, React, TypeScript, and Express, with sound judgment on when to use each stack Deep knowledge of SQL and experience with distributed messaging and streaming systems such as Kafka, SQS, SNS, or RabbitMQ Solid cloud experience with AWS, GCP, or Azure, including infrastructure as code, CI/CD, and observability Ability to navigate ambiguity, make principled trade-offs, and lead without formal authority Experience working in remote, asynchronous, distributed teams with strong written and verbal communication skills Curiosity and enthusiasm for emerging technologies and their real-world applications
Nice to Haves:
Hands-on experience working with large language models and techniques to improve reliability, latency, and cost efficiency Experience in regulated or compliance-heavy industries such as insurance, finance, or healthcare Background in high-growth startup environments where systems and teams scaled rapidly Proven track record of mentoring senior and mid-level engineers Public technical contributions through open source, talks, or publications
Why This Role:
Strong funding, long runway, and clear momentum toward category leadership Ownership over foundational systems that define how autonomous AI agents operate in production High autonomy and trust with direct influence on long-term technical direction A collaborative, high caliber engineering culture that values rigor, learning, and impact The opportunity to help define a new category of applied AI systems used by real customers at scale
If you are excited by the chance to shape the core architecture of an AI platform operating in the real world, this role offers both the scope and the ownership to make a lasting impact.
Location:
San Francisco or Boston Compensation:
$220k - $240k Employment Type:
Full time Model:
Hybrid (days on site, 3 days remote)
This company is building AI agents that automate complex, manual workflows across one of the largest and most operationally complex industries in the world. What started with voice, the hardest and highest impact interface, is rapidly expanding into full end-to-end workflow automation across sales, servicing, and claims. The long term vision is to create reasoning agents capable of operating autonomously across entire enterprise systems.
With over $70M raised, including a recent large Series B led by top tier venture firms, the company is entering a phase of rapid scale. Engineering is the core of the business, and technical decisions made today will define how intelligent systems operate in real production environments for years to come.
The Opportunity:
As a Staff Software Engineer, you will be a senior technical leader responsible for shaping foundational systems that power AI-driven products at scale. This role goes far beyond feature delivery. You will own architectural direction, influence platform strategy, and build systems that enable reliable, observable, high-performance AI agents in a regulated, mission-critical environment.
You will work with an elite group of engineers, researchers, and product leaders who value strong technical judgment, clear communication, and high ownership. This is a role for someone who thrives in ambiguity, enjoys solving hard infrastructure problems, and wants to see their work have immediate, real world impact.
What You Will Do:
Define and drive the technical vision for core platforms and domains, including architecture, infrastructure, tooling, and performance Design, build, and operate scalable backend systems that leverage foundational LLMs and asynchronous workflows Lead architectural decisions and trade-offs, balancing speed of iteration with long-term reliability and maintainability Partner closely with product, data science, and infrastructure teams to translate business strategy into durable technical roadmaps Serve as a technical mentor through design reviews, code reviews, and hands-on guidance, raising the bar for engineering excellence Own operational excellence across the stack, including debugging complex issues, participating in on-call, and leading post-mortems Define, measure, and improve reliability metrics such as SLAs, SLOs, and SLIs Identify technical debt and drive initiatives that improve system quality, performance, and developer velocity Introduce new technologies and processes that materially improve how teams build and ship software Represent the engineering organization externally when appropriate through technical talks, open source, or partner engagement
What Were Looking For:
8+ years of experience building and operating high-quality production software, with strong depth in Python Demonstrated experience architecting asynchronous, distributed, high-throughput systems in production Strong expertise with Python frameworks such as FastAPI, Django, and asyncio or equivalent Proficiency with Node.js, React, TypeScript, and Express, with sound judgment on when to use each stack Deep knowledge of SQL and experience with distributed messaging and streaming systems such as Kafka, SQS, SNS, or RabbitMQ Solid cloud experience with AWS, GCP, or Azure, including infrastructure as code, CI/CD, and observability Ability to navigate ambiguity, make principled trade-offs, and lead without formal authority Experience working in remote, asynchronous, distributed teams with strong written and verbal communication skills Curiosity and enthusiasm for emerging technologies and their real-world applications
Nice to Haves:
Hands-on experience working with large language models and techniques to improve reliability, latency, and cost efficiency Experience in regulated or compliance-heavy industries such as insurance, finance, or healthcare Background in high-growth startup environments where systems and teams scaled rapidly Proven track record of mentoring senior and mid-level engineers Public technical contributions through open source, talks, or publications
Why This Role:
Strong funding, long runway, and clear momentum toward category leadership Ownership over foundational systems that define how autonomous AI agents operate in production High autonomy and trust with direct influence on long-term technical direction A collaborative, high caliber engineering culture that values rigor, learning, and impact The opportunity to help define a new category of applied AI systems used by real customers at scale
If you are excited by the chance to shape the core architecture of an AI platform operating in the real world, this role offers both the scope and the ownership to make a lasting impact.