Senior Software Engineer - Reference Data
Build and productionize AI-native products and platform components, including LLM and agentic systems, while driving scalable architecture, operational excellence, and rapid iteration. The role requires extensive software engineering experience and a track record of shipping complex production systems.
About the job
Responsibilities
- Drive the end-to-end execution and delivery of AI-native products, from initial prototype to scalable production services.
- Architect, build, and productionize core components of the AI platform, including:
- LLMs and the surrounding ecosystem, such as vector databases and prompt tuning.
- Agentic frameworks.
- Core agent capabilities, including MCP, cross-platform tool use, web browsing, and computer use.
- Enforce technical discipline and operational excellence across AI products.
- Rapidly iterate on AI products using performance metrics and user feedback.
- Lead evaluation and adoption of new AI technologies and frameworks.
- Partner with product managers and engineering teams to translate strategic goals into technical solutions and abstract AI complexity for rapid iteration.
- Collaborate with engineering leads to define and implement scalable platform architecture.
- Evaluate and drive strategic business and technology decisions for the company and its customers.
- Provide technical leadership, education, best-practice sharing, and strategic guidance.
Requirements
- Bachelor's or master's degree in Computer Science, Statistics, Mathematics, or another quantitative or technical field, or equivalent practical experience.
- Extensive software engineering experience.
- Proven track record of owning and shipping complex, production-grade systems.
- Experience shipping and maintaining AI-native products or features, or significant personal AI projects.
- Strong ownership mindset and commitment to completing projects and raising execution standards.
- Bias for action and passion for rapid shipping and iteration.
Nice-to-Haves
- Experience with LLMs and agentic systems.
- Hands-on experience with modern AI/LLM technologies such as Databricks, LangChain, or MLflow.
- Advanced understanding of the probabilistic systems underpinning modern LLMs.
- Experience building AI products in highly accuracy-sensitive domains such as finance.
Skills
Artificial Intelligence, LLMs, Vector Databases, Prompt Tuning, Agentic Systems, Mcp, Web Browsing, Computer Use, Databricks, LangChain, MLflow, Machine Learning
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