Staff Software Developer, Syndio

• Proficiency developing clean modular and efficient code with Python
• Track record building and deploying AI systems within Google Cloud Platform, familiarity with BigQuery, Firebase, and Vertex AI
• Working knowledge of Google Gemini, OpenAI, and Anthropic APIs
• Familiarity with evaluation methodologies for assessing LLM accuracy, hallucinations, and task-specific performance
• Exposure to—or strong interest in—vector databases, semantic search, agent frameworks, and protocols like MCP for connecting AI systems to external tools and data sources
• Fluent with AI-assisted development tools (Cursor, Claude Code, GitHub CoPilot)
• Foundational knowledge of machine learning concepts, model architectures, and LLM capabilities and constraints
• Natural curiosity and passion for staying current with rapidly evolving AI technologies
• Ability to balance innovation with practical business requirements
• Adaptable when navigating ambiguity and rapidly shifting priorities
• Comfortable communicating technical concepts and trade-offs to non-technical stakeholders
• At Syndio, we're building a diverse team that values candor, curiosity, and community. If you share these values and are interested in joining us, we'd love to talk with you even if you don't 100% meet the "about you" listed here. We don't expect anyone to have all the answers, as long as you're willing to learn and grow with us

Desirable

• We are seeking a talented Staff-level AI Developer to join our applied AI team. In this role, you will be responsible for designing, building, and scaling our AI systems that solve complex problems related to compensation and compliance
• You’ll work closely in a cross-functional squad that includes data scientists, software engineers, product managers, and business stakeholders
• You will have the opportunity to work at the forefront of AI innovation–exploring emerging tools and techniques while translating them into production-ready solutions that deliver real business impact
• Design, develop, and deploy production AI/ML systems that deliver business impact to our customers
• Build and maintain LLM-based applications leveraging context engineering techniques and toolsets
• Collaborate with data scientists to transition approved proof of concepts from a research environment into production
• Integrate AI capabilities into existing products and services through APIs and microservices
• Design and implement evaluation frameworks to assess model accuracy, reliability, and task-specific performance
• Monitor production performance and implement optimizations based on evaluation metrics and real-world usage patterns
• Stay up-to-date with the rapid changes in the AI landscape (e.g., new foundation models, quantization techniques) and prototype new ideas quickly
• Month 1: Immediate Impact
• From day one, you'll be immersed in our platform, infrastructure, and codebase. We expect a rapid learning curve and the ability to quickly contribute. A key deliverable for your first month will be deploying a feature that demonstrates your grasp of our systems and your ability to execute effectively
• Month 2: Proactive Contribution
• You'll move beyond the initial learning phase and take a proactive role in identifying opportunities for improvement. This will involve deep dives into our endpoints, independent problem-solving, and a demonstrated ability to iterate and enhance our product
• Month 3: Driving Innovation
• By the third month, you'll be a fully integrated member of our AI team, operating at full capacity. This includes active participation in technical discussions, independent execution of complex tasks, and the ability to propose and implement innovative technical solutions

• Below you'll find an outline of the interview plan for our Staff AI Developer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision
• 30 min - Phone call with a member of our Talent Team
• 75 min - Zoom interview with the Hiring Manager
• Skills Evaluation - Take-home Assignment
• 75 hr - Technical Interview with Team
• 30 min - Executive Interview