Sr. AI Engineer
Senior individual contributor building and scaling production LLM-powered services and autonomous AI agents for accounting automation software. Owns full lifecycle from prototype through deployment and maintenance.
How You’ll Make an Impact
- Build and scale production LLM-powered services, including context engineering, prompt design, and agentic workflows
- Develop and operate autonomous AI agents, owning the full lifecycle from prototype to ongoing maintenance
- Design and execute evaluations for AI/ML systems to drive architectural decisions and share findings cross-functionally
- Contribute to shared AI platforms and internal tooling that enable other teams to deploy and monitor AI features
- Write production-grade Python code designed for long-term extensibility and team ownership
- Serve as a technical consultant to product and UX teams on AI feasibility, tradeoffs, and architecture
- Monitor and optimize AI/ML services for latency, cost-efficiency, and high-volume throughput
- Troubleshoot production system health and identify solutions to reduce technical debt and performance degradation
- Design AI capabilities with strict adherence to data privacy and compliance standards for financial data
- Stay current on emerging AI/ML techniques to raise the collective engineering standard of the team
The Expertise You’ll Bring
- 3+ years of professional software or AI/ML engineering experience with a focus on production LLM services
- Proven track record of developing, running, and evaluating autonomous agents in a production environment
- Strong Python proficiency with the ability to write clean, maintainable, and reliable code
- Solid understanding of agent architectures and the ability to resolve system failures under time pressure
- Knowledge of performance optimization, including latency, throughput, and cost management for AI services
- Familiarity with data privacy and compliance considerations for systems handling sensitive financial data
- Experience with various LLM models (OpenAI, Anthropic, open-source) and modern AI development tools
- Ability to communicate complex technical concepts and tradeoffs to both technical and non-technical partners
- Minimum of a four-year degree in Computer Science, Engineering, Mathematics, or equivalent experience
Preferred Experience
- Full end-to-end AI/ML lifecycle experience including ideation, deployment, and maintenance at scale
- Practical experience with the AWS AI/ML stack and document processing using LLMs
- Experience mentoring other engineers and familiarity with uv for Python project management
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