Staff Software Engineer, AI Lab Execution System (AI)

TL;DR

Staff Software Engineer, AI Lab Execution System (AI): Developing systems to handle diverse workloads and scale seamlessly, including structured SQL database, data lake houses, and vector databases with an accent on front-end and backend expertise. Focus on building performant and elegant systems for a cutting-edge AI platform with real scientific impact.

Location: Cambridge, MA USA; San Francisco, CA USA

Salary: $192,000 - $238,000 USD

Company

hirify.global is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.

What you will do

• Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 4-6 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend or data modeling and design.
• Strong experience with React and Typescript is required.
• Strong experience with SQL, NoSQL, and emerging database technologies (e.g., Vector DBs); proven track record in schema design, indexing, and query optimization.
• Proven ability to design and scale RESTful or GraphQL APIs with a focus on reliability and performance.
• Hands on experience using AI coding assistants to drive productivity is required.

Nice to have

• Experience working with life sciences, material sciences, or other research-heavy fields.
• Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with orchestration tools (Flyte, Temporal, Airflow, Prefect, etc.).

Culture & Benefits

• Competitive compensation including bonus potential and generous early equity.
• Committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.