Senior Software Engineer, AI

Syllo is on a mission to transform litigation with its AI-powered litigation workspace designed for legal professionals. They are seeking a skilled Senior Software Engineer focused on the practical application of AI to build robust and scalable features that enhance user experience.

Responsibilities:

• System Design & Implementation: Design and build high-performance, production-level AI-powered features and services, with a focus on reliability and scalability
• Develop robust engineering solutions to mitigate the inherent unreliability of LLMs. This includes implementing effective guardrails, validation pipelines, error handling, caching, and failover/fallback mechanisms to ensure a high-quality user experience even when the model misbehaves
• Focus on optimizing latency, throughput, and cost efficiency for all AI-powered services
• Serve as an engineering expert in integrating models and data feeds with existing business logic and APIs
• Champion and enforce high standards for code quality, architectural design, and system documentation
• Implement rigorous testing strategies, including unit, integration, and performance testing, to ensure the robustness of AI features before and after deployment
• Participate actively in peer code reviews to maintain a high bar for engineering standards across the team
• Take ownership of the full lifecycle of new AI features, from initial design and prototyping to testing and deployment into the production environment
• Own the end-to-end development of new features, including API design, integration with front-end services, persistent data storage, and comprehensive monitoring/alerting
• Work closely with product managers and other engineers to scope, estimate, and deliver features on a fast iterative cycle
• Quickly onboard onto our existing codebase to understand, maintain, and significantly enhance existing data and feature pipelines, improving their efficiency and robustness
• Embrace and utilize AI-powered developer tools (such as GitHub Copilot) to maximize your efficiency, demonstrate a commitment to continuous learning, and set a high bar for engineering velocity

Requirements:

• Deep Engineering Fluency & Quality Focus: Proven ability to build and deploy complex, high-quality software systems with an emphasis on maintainable code, rigorous testing, and engineering best practices
• Python Proficiency: Fluent in Python and its ecosystem for backend services and data processing
• System Design Expertise: Strong grasp of system design principles, including distributed systems and API design
• Demonstrated ability to design scalable distributed systems, including expertise in microservices architecture
• Codebase Agility: Excellent ability to read, understand, and navigate an unfamiliar codebase quickly
• Fast Learner: A demonstrable history of rapidly acquiring new technical skills and applying them to solve business problems
• AI/ML Feature Experience: Experience directly building, shipping, and maintaining AI-powered products, agents, or intelligent features in a commercial setting
• LLM/Generative AI Exposure: Familiarity with the unique engineering challenges of integrating Large Language Models into a production environment
• Hands-on experience with LLM operationalization challenges (MLOps for LLMs), including prompt engineering, working with vector databases, RAG systems, or managing context windows
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) for deploying and managing services