# Principal Software Engineer, Applied AI at Lila Sciences > United States · Principal · Software engineering · open. Source: https://alderhq.app/jobs/greenhouse%3Alilasciences%3A4031455009 (read 2026-11-13). ## Facts (observed) - Company: [Lila Sciences](https://alderhq.app/companies/lila-sciences) - Location text: Cambridge, MA USA; San Francisco, CA USA; One Charles Park, Cambridge, MA; San Francisco, CA - Where it can be done from (inferred): United States (evidence: "Location: Cambridge, MA USA; San Francisco, CA USA; One Charles Park, Cambridge, MA; San F") - Posted: 2025-10-06 (403 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-12 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://job-boards.greenhouse.io/lilasciences/jobs/4031455009 - Skills listed (inferred): Python, Django, FastAPI, AWS, Kubernetes, Docker, Terraform, SQL, LLMs, Distributed systems ## Pay and sponsorship - Posted pay: $204k–$310k per year (from the listing's pay field) - Market band for similar posted roles (Boston, n 41): p25 $200k, median $235k, p75 $263k - H-1B filings at this company for similar roles, FY26: 5, median offered wage $115k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) ## Description (the employer's text) ### 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 --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Alilasciences%3A4031455009 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.