Job description

As a Senior Software Engineer on this team, you will design, build, and ship software systems that apply AI to to improve the efficiency of the PACE team. You will work in small iterations, delivering working software early and often, and use data to guide what to build next. You believe that quality is built in - not bolted on - and that fast delivery and high standards reinforce each other. You will help establish the engineering culture of a new team: lean practices, continuous delivery, production observability, and a relentless focus on outcomes over output. You are deeply curious - about about emerging AI capabilities, how users actually work, and how to make tools to enable success - and you channel that curiosity into building things that matter. You will collaborate closely with PACE domain experts to deeply understand their problems, and with data and AI practitioners to build systems that genuinely work at scale. Bachelor's Degree in Computer Science, Computer Engineering, related field, or equivalent work experience 7+ years experience building and shipping production software systems Strong track record of delivering AI-powered systems at scale, including model integration, evaluation, and production monitoring Deep practical experience with modern software engineering practices: continuous integration, continuous delivery, trunk-based development, and incremental delivery Proficient in Python and at least one other high-level programming language Experience building data pipelines and working with connected data across multiple sources Experience with cloud infrastructure and container technologies including Kubernetes and Docker Demonstrated ability to build observability into production systems - metrics, tracing, logging, and alerting A curious mindset - you dig into unfamiliar domains, ask why things work the way they do, and seek out knowledge beyond your immediate responsibilities Excellent written and verbal communication skills with both technical and non-technical audiences Master's degree in Computer Science, Computer Engineering, related field, or equivalent work experience Experience working in or building software for regulated industries (compliance, legal, safety, or similar domain) Familiarity with the principles in Accelerate and practical experience improving DORA metrics in a team setting Experience with test-driven development, continuous refactoring, small batch delivery, and collective code ownership Experience securing AI/LLM systems that process sensitive or regulated data, including prompt injection defense, data handling policies, and audit trail requirements Experience with LLM application patterns: retrieval-augmented generation, prompt engineering, evaluation frameworks, and human-in-the-loop workflows Experience with MLOps practices including model versioning, experiment tracking, and performance monitoring in production Track record of building systems that connect and make sense of heterogeneous data sources at enterprise scale Experience helping establish engineering culture on a new or transforming team

Requirements

Must-haves

Bachelor's Degree in Computer Science, Computer Engineering, related field, or equivalent work experience
7+ years experience building and shipping production software systems
Strong track record of delivering AI-powered systems at scale, including model integration, evaluation, and production monitoring
Deep practical experience with modern software engineering practices: continuous integration, continuous delivery, trunk-based development, and incremental delivery
Proficient in Python and at least one other high-level programming language
Experience building data pipelines and working with connected data across multiple sources
Experience with cloud infrastructure and container technologies including Kubernetes and Docker
Demonstrated ability to build observability into production systems - metrics, tracing, logging, and alerting
A curious mindset - you dig into unfamiliar domains, ask why things work the way they do, and seek out knowledge beyond your immediate responsibilities
Excellent written and verbal communication skills with both technical and non-technical audiences
Master's degree in Computer Science, Computer Engineering, related field, or equivalent work experience
Experience working in or building software for regulated industries (compliance, legal, safety, or similar domain)
Familiarity with the principles in Accelerate and practical experience improving DORA metrics in a team setting
Experience with test-driven development, continuous refactoring, small batch delivery, and collective code ownership
Experience securing AI/LLM systems that process sensitive or regulated data, including prompt injection defense, data handling policies, and audit trail requirements
Experience with LLM application patterns: retrieval-augmented generation, prompt engineering, evaluation frameworks, and human-in-the-loop workflows
Experience with MLOps practices including model versioning, experiment tracking, and performance monitoring in production
Track record of building systems that connect and make sense of heterogeneous data sources at enterprise scale
Experience helping establish engineering culture on a new or transforming team

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aipythonkubernetesdockerllm

Platform: apple
Effort: medium