Senior Principal Software Engineer
About The Position
We are seeking a Senior Principal Software Engineer to join our software group and help build the next generation of our AI-driven scientific platform. In this role, as a technical leader, you will collaborate closely with ML researchers, platform engineers, and scientists to develop applications and services capable of supporting AI driven scientific process. You will also ensure seamless collaboration across diverse teams. You’ll have the opportunity to shape a modern, production-grade system from the ground up, working across a toolbox that includes cutting-edge AI frameworks, lab automation software, and scalable cloud infrastructure. In our fast-paced environment, your technical expertise and creative problem-solving will push the boundaries of what’s possible in AI-driven science. This is a unique chance to be at the forefront of applied AI in scientific research. If you are passionate about building intelligent systems that can transform science, we would love to hear from you! Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 12+ years of experience successfully building and deploying scalable software systems in production environments.
- Technical Leadership: Experience leading and mentoring a team and making key architecture decisions. 0→1 product development experience is required.
- Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic, Apache Iceberg, DuckDB)
- Cloud & DevOps Knowledge: Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes, infrastructure-as-code (Terraform), and CI/CD pipelines (GitHub Actions).
- Communication & Collaboration: Leadership skills working cross functionally. Strong verbal and written communication. Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
Nice To Haves
- Hands-On with Latest AI Tools: Exposure to AI technologies such as LLMs or agentic frameworks, as well as experience leveraging AI to improve development performance.
- Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
- Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Flyte).
- Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
- Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
Responsibilities
- Lead End-to-End Software Development Lifecycle: Drive the technical design, implementation, and maintenance of software systems and applications.
- Architect & Implement Applications: Design and build robust, scalable web applications and services across the full stack, empowering scientists to harness AI in their research workflows.
- Collaborate Cross-Functionally: Partner with domain scientists, ML engineers, and product leads to integrate various technologies—ML models, data/compute infrastructure, and experimental automation tools.
- Establish Organizational Best Practices: Set standards for code quality, testing, and documentation. Mentor junior engineers and foster a culture of knowledge sharing.
- Operationalize Code in Production: Leverage observability tooling to monitor real world performance and steer improvements.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
