Staff Software Engineer, AI Lab Execution System

Lila Sciences; Cambridge (MA); On-site; USD 192,000 - 238,000; Full time

Job summary

Lila Sciences, located in Cambridge, MA, is seeking a Staff Software Engineer for AI Lab Execution System to design and optimize data-driven applications. In this role, you will build modern systems integrating AI with scientific workflows.

The ideal candidate will have significant experience in engineering, especially with React, Typescript, and a strong understanding of databases. Competitive compensation, including bonus potential and equity, is offered.

Qualifications

• 4–6 years of engineering experience building and deploying large-scale systems.
• Strong experience with React and Typescript is required; proficiency in Python is also needed.
• Proven experience with SQL, NoSQL, and emerging database technologies.

Responsibilities

• Design and build UI and APIs that integrate with AI-driven applications.
• Drive the implementation of front-end and backend services with a focus on performance.
• Diagnose and optimize system bottlenecks, ensuring high availability.

Skills

React

Typescript

Python

SQL

NoSQL

Schema design

RESTful APIs

GraphQL

DevOps practices

Collaboration

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Tools

AWS

Kubernetes

GCP

Azure

Terraform

CloudFormation

GitHub Actions

Job description

Your Impact at LILA

We are seeking a Staff Software Engineer - AI Lab Execution System to join our software group and help build the next generation AI-driven scientific platform. In this role, you will design, build, and optimize intelligent, data-driven applications front‑end. You will focus on developing UI, services, high-performance APIs, databases, and ensuring the reliability of services that integrate advanced AI frameworks with complex scientific analytics and laboratory workflows.

You’ll work closely with ML researchers, platform engineers, and scientists to develop systems that can handle diverse workloads and scale seamlessly, including structured SQL databases, data lake houses, and vector databases. This is an opportunity to apply your deep front‑end and backend expertise to a cutting‑edge AI platform with real scientific impact. If you are passionate about building performant and elegant systems, we would love to hear from you.

What You’ll Be Building

• Design and build 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.

What You’ll Need To Succeed

• 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; proficiency in Python is also needed.
• Proven experience with SQL, NoSQL, and emerging database technologies (e.g., vector DBs); demonstrated skill 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.
• Experience working with life sciences, material sciences, or other research‑heavy fields.
• Excellent communication and collaboration skills, with a track record of working cross‑functionally with scientists, data engineers, and product teams; ability to explain complex ideas to diverse audiences.
• Strong problem‑solving skills with the ability to take ownership of complex backend challenges, balancing scalability, performance, and maintainability.

Bonus Points For

• Hands‑on experience with AWS, GCP, or Azure; strong understanding of Kubernetes, containerization, infrastructure‑as‑code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with orchestration tools (Flyte, Temporal, Airflow, Prefect, etc.).

Compensation

We offer competitive compensation including bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.

Expected Base Salary Range: $192,000 USD – $238,000 USD