Senior Software Engineer, Applied AI
AI summary of the role
Senior Software Engineer in the Applied AI group, building backend systems and data pipelines for an autonomous scientific AI platform.
What you’ll do
- Design and deploy backend services and data pipelines supporting LLMs, RAG, and agentic frameworks
- Build high-performance APIs and microservices for AI model integration
- Architect scalable data pipelines for structured, unstructured, and vectorized data
- Implement and optimize SQL, NoSQL, and vector databases for low-latency AI retrieval
What you’ll bring
- 7+ years building and scaling production systems including APIs, data pipelines, and distributed services
- Strong Python skills (FastAPI, Flask, Django) with backend service development experience
- Proven experience with SQL, NoSQL, and vector databases
- Hands-on experience integrating ML models or AI-driven workflows into production
Technologies
Python · FastAPI · Flask · Django · AWS · Kubernetes · Terraform · CloudFormation · RAG · LLM · vector databases
About Lila Sciences
Autonomous AI platform that executes the scientific method end-to-end—from hypothesis generation to experimental execution—for biotech, materials, and chemical R&D.
Series A
Source and classification
Internal deployment & tooling · Evidence for this classification:
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 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!
More from the job description
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 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 da [... source excerpt omitted ...] 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 [... source excerpt omitted ...] 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 adaptabili
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