Senior Software Engineer, Applied AI

🚀 About Lila Sciences

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    

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

🌟 Your Impact at Lila

We are seeking a Senior Software Engineer to join our Applied AI group and help build the next generation of our AI-driven scientific platform. In this role, you will collaborate closely with ML researchers, platform engineers, and scientists to develop agent-driven applications capable of executing complex tasks autonomously. 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, integrating cutting-edge AI frameworks with 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.

🛠️ What You'll Be Building

• Lead End-to-End Implementation: Drive the technical design and implementation of AI systems, creating a scalable, extensible framework that powers iterative R&D workflows.
• Contribute to Agentic AI Platform: Design, develop, and maintain systems leveraging large language models for intelligent decision-making. Orchestrate workflows, gather data, and refine scientific designs.
• Architect & Implement ML Pipelines: Build and maintain end-to-end data and machine learning pipelines to facilitate a robust data environment for agentic interactions.
• 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.
• Develop Best Practices for Agentic Systems: Establish design patterns for planning, tool selection, and evaluation, ensuring high-performance outcomes.
• Optimize Performance & Reliability: Profile and optimize agentic workflows for throughput, fault-tolerance, and cost efficiency. Implement logging, monitoring, and alerting to ensure production readiness.
• Champion Best Practices: Set standards for code quality, testing, and documentation. Mentor junior engineers and foster a culture of knowledge sharing.

🧰 What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience successfully building and deploying scalable software systems in production environments.
• Cloud & DevOps Knowledge: Hands-on experience with AWS, GCP, or Azure; strong understanding of containerization (Docker/Kubernetes), infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines.
• Workflow Orchestration: Familiarity with modern orchestrators (Temporal, Airflow, etc.) to coordinate complex data and ML pipelines.
• Data Engineering: Ability to design robust data flows and handle large volumes of structured/unstructured data, including performance optimization.
• Communication & Collaboration: Proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.

✨ Bonus Points For

• Experience in AI/ML Pipelines: Prior work building or optimizing ML pipelines (training, evaluation, deployment); experience monitoring model performance in production.
• Hands-On Familiarity with Latest AI Concepts: Exposure to AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or agentic frameworks—and how they integrate into a software platform.
• Domain Background: Exposure to life sciences, material sciences, or related fields.
• Technical Leadership: Experience leading or mentoring a team and making key architecture decisions.

🌈 We’re All In

Lila Sciences is 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.

🤝 A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.