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# Senior Software Engineer, Applied AI

- **Company:** Lila Sciences, Inc.
- **Location:** Cambridge, MA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Computer Programming, Databases, Continuous Integration, Database Applications, DevOps, Django Web Framework, Fault Tolerance, Python (Programming Language), Knowledge-Based Systems, Machine Learning, NoSQL, Query Optimization, Service Development Studio, Software Engineering, SQL Databases, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Generative AI, Indexer, Backend, Agentic-AI, Cloudformation, Fastapi, AI Platforms, Kubernetes, Information Technology, Low Latency, Machine Learning Operations, Terraform, Data Pipelines, Docker, Microservices
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25303_7d1bf8a7f413851605190de8aa93814a

## About the Role

* 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.

## Description

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!, * 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.