Job description

Your Impact at LILA We are seeking a Principal 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 design and optimize the backend systems, data pipelines, and AI integrations that power intelligent, data-driven applications. You’ll work at the intersection of backend engineering and machine learning, ensuring our platform seamlessly scales and supports cutting-edge applied AI techniques such as Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration. This role is ideal for someone who thrives in bridging software engineering and applied AI—turning research into production-grade systems that drive real-world scientific discovery. If you are passionate about building performant, elegant systems that make AI useful and impactful, we would love to hear from you! What You'll Be Building Applied AI Integration: Design and deploy backend services and data pipelines that directly support advanced AI applications, including LLMs, RAG, and agentic frameworks. API & Service Development: Build high-performance APIs and microservices that enable seamless integration between AI models, scientific tools, and user-facing applications. Data Pipeline Architecture: Architect and manage scalable pipelines capable of handling structured, unstructured, and vectorized data for AI/ML workloads. Database & Knowledge Systems: Implement and optimize SQL, NoSQL, and vector databases to support low-latency AI retrieval and inference workloads. Cloud & Infrastructure: Leverage AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to build robust, production-ready AI platforms. Performance & Reliability: Diagnose system bottlenecks, optimize for cost and speed, and ensure the reliability and fault-tolerance of AI-driven workflows. Collaboration: Partner with ML researchers, platform engineers, and scientists to translate models and algorithms into scalable, production-ready systems. What You’ll Need to Succeed Educational Background: Bachelor’s or Master’s in Computer Science, Engineering, or a related field. Backend & Data Expertise: 7+ years of professional experience building and scaling production systems, including APIs, data pipelines, and distributed services. Programming Skills: Strong Python skills (FastAPI, Flask, Django), with solid experience in backend service development. Databases: Proven experience with SQL, NoSQL, and vector databases; skilled in schema design, indexing, and query optimization. Applied AI Systems: Hands-on experience integrating ML models or AI-driven workflows into production services. Cloud & DevOps: Proficiency with AWS, Docker/Kubernetes, CI/CD pipelines, and infrastructure-as-code. Communication & Problem-Solving: Ability to work cross-functionally with diverse teams and explain complex technical concepts to non-experts. Bonus Points For Scientific & Data-Intensive Domains: Experience working with life sciences, materials sciences, or other research-heavy fields. Startup Experience: Comfort with fast-paced, iterative environments where impact and adaptability matter. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $204,000 — $310,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. 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. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . 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.

Requirements

Must-haves

Your Impact at LILA
What You'll Be Building
Applied AI Integration: Design and deploy backend services and data pipelines that directly support advanced AI applications, including LLMs, RAG, and agentic frameworks.
API & Service Development: Build high-performance APIs and microservices that enable seamless integration between AI models, scientific tools, and user-facing applications.
Data Pipeline Architecture: Architect and manage scalable pipelines capable of handling structured, unstructured, and vectorized data for AI/ML workloads.
Database & Knowledge Systems: Implement and optimize SQL, NoSQL, and vector databases to support low-latency AI retrieval and inference workloads.
Cloud & Infrastructure: Leverage AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to build robust, production-ready AI platforms.
Performance & Reliability: Diagnose system bottlenecks, optimize for cost and speed, and ensure the reliability and fault-tolerance of AI-driven workflows.
Collaboration: Partner with ML researchers, platform engineers, and scientists to translate models and algorithms into scalable, production-ready systems.
What You’ll Need to Succeed
Educational Background: Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
Backend & Data Expertise: 7+ years of professional experience building and scaling production systems, including APIs, data pipelines, and distributed services.
Programming Skills: Strong Python skills (FastAPI, Flask, Django), with solid experience in backend service development.
Databases: Proven experience with SQL, NoSQL, and vector databases; skilled in schema design, indexing, and query optimization.
Applied AI Systems: Hands-on experience integrating ML models or AI-driven workflows into production services.
Cloud & DevOps: Proficiency with AWS, Docker/Kubernetes, CI/CD pipelines, and infrastructure-as-code.
Communication & Problem-Solving: Ability to work cross-functionally with diverse teams and explain complex technical concepts to non-experts.
Scientific & Data-Intensive Domains: Experience working with life sciences, materials sciences, or other research-heavy fields.
Startup Experience: Comfort with fast-paced, iterative environments where impact and adaptability matter.

Nice-to-haves

Bonus Points For

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aimachine learningllmapimlsqlawskubernetespythondockerci/cd

Platform: greenhouse
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Benefits

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Vision

Parental Leave