Responsibilities
- Design, build, and deploy production-grade systems leveraging Large Language Models (LLMs) from providers like OpenAI, Google (Vertex AI), and Anthropic.
- Develop and scale end-to-end applications for complex document understanding, focusing on textual, financial, and tabular data. This includes building sophisticated, high-precision RAG (Retrieval-Augmented Generation) systems that are battle-tested for production traffic.
- Implement robust guardrails, validation layers, and monitoring to preemptively address model limitations, such as hallucinations, both in offline evaluation and online production environments.
- Engineer and deploy complex, multi-step AI agents, with a focus on creating agentic workflows that are scalable, maintainable, and secure, especially when handling highly sensitive client data.
- Own projects from conception to deployment, making key architectural decisions and ensuring the systems you build meet stringent requirements for latency, precision, and recall.
- Build scalable ETL (Extract, Transform, Load) data pipelines to process and prepare complex datasets for AI model consumption.
- Collaborate closely with product managers, software engineers, and other scientists to build tools, define metrics, and continuously improve the end-to-end quality of our AI systems.
- Align your technical work with business outcomes, effectively communicating the impact and performance of the systems you build to stakeholders.
Requirements
- A degree in Computer Science, Engineering, or a related quantitative field (or equivalent practical experience).
- Proven experience building and shipping software in a production environment.
- Strong software engineering fundamentals, including data structures, algorithms, system design, and writing clean, maintainable code.
- Hands-on experience building, deploying, and maintaining production-level agent systems using frameworks like Agent Development Kit (ADK) or LangGraph.
- Proficiency in Python and a strong aptitude for working in a polyglot environment that may include TypeScript, C#, etc.
- Experience developing applications that consume and integrate APIs from major AI providers (e.g., Google Vertex AI, Azure OpenAI).
Nice to Have
- 5+ years of professional experience writing production code and shipping AI/ML-powered features.
- Demonstrated experience building and scaling agentic workflows.
- Experience working in a highly regulated industry such as LegalTech, FinTech, or HealthTech.
- Experience with MLOps, including setting up training pipelines, monitoring model performance in production, and implementing CI/CD for ML systems.
- Familiarity with techniques for ensuring data privacy and security in AI systems (e.g., identifying and sanitizing PII).
Benefits
- Competitive salary.
- Hybrid work arrangement if located in the Phoenix or New York area; otherwise, fully remote. We also meet together in person several times a year.
- Excellent medical, dental, and vision insurance options, with low-cost premium structures that demonstrate our commitment to offering great value to our employees.
- 100% company-paid basic life insurance, short-term and long-term disability insurance.
- 100% paid parental leave upon eligibility.
- Company equity managed through Carta.
- 401k with match and 100% vesting upon hire.
- Flexible PTO in an environment where taking time off to relax or recharge is supported and encouraged. Take time off for holidays—and yes, your birthday counts too. Celebrate, relax, and recharge without thinking twice.
