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AI Summary
Build and scale the core intelligence layer of TaxGPT by designing agentic workflows and AI-powered product experiences for tax automation. Develop and maintain evaluation benchmarks and regression tests to ensure the reliability, accuracy, and safety of AI outputs.
About TaxGPT
TaxGPT is revolutionizing the tax and accounting space with AI-driven solutions tailored for accountants, tax professionals, and SMBs. We are building an AI co-pilot to transform tax workflows, drive efficiency, and simplify compliance. Recently named one of Business Insider's 30 Early-Stage Startups Most Likely to Become Tech's Next Unicorns, we would love for you to join our growing team.
Benefits: Medical, dental, vision, 401k + 3% match, life insurance
About the Role
We are looking for a Senior AI Engineer to help build the core intelligence layer behind TaxGPT. This role is focused on improving how effectively, reliably, and safely AI can automate real tax workflows using LLMs, retrieval systems, structured context, and agentic workflows.
You will work closely with software engineers, product teams, and technical leadership to design, build and scale AI systems that support fast development, stable production environments, and long-term scalability.
This is a senior individual contributor role for someone who can work with high autonomy, move quickly from prototype to production, and bring strong judgment to applied AI product development.
What You'll Do
AI Systems and Agentic Workflows
- Build and improve AI-powered product experiences for tax and accounting workflows
- Increase automation rates across workflows while maintaining accuracy, reliability, and a strong user experience
- Design and refine prompt-based systems, tool-using agents, and multi-step workflows that perform well in real production use cases
- Prototype and ship end-to-end AI features quickly, from idea to working product
- Design workflows that combine LLMs, tools, APIs, retrieval systems, and structured outputs in a robust way
- Work across APIs, tools, retrieval layers, and backend systems to make AI capabilities useful in real user workflows
Model Quality, Evals, and AI Reliability
- Build and maintain evals, regression tests, and benchmarks that help us measure and improve AI quality over time
- Define practical metrics for usefulness, accuracy, latency, reliability, and cost
- Investigate model failures and systematically improve performance through better prompting, context design, routing, and system architecture
- Contribute to fine-tuning experiments, benchmark design, and dataset development where it adds product value
Applied Engineering & Technical Leadership
- Write strong Python code for prototypes, internal tooling, backend services, and AI workflows
- Work with product and backend engineers to productionize AI systems cleanly and safely
- Use data and experimentation to guide decisions, validate improvements, and prioritize the highest-impact work
- Help build feedback loops that make AI behavior easier to understand, debug, and improve over time
- Make strong technical decisions in your area and help the team balance speed, quality, and maintainability
- Share clear guidance through code reviews, design discussions, and documentation
What We're Looking For
Required Qualifications
- 5+ years of experience in software engineering, machine learning engineering, AI engineering or a related role
- Strong experience building with LLMs in real products, not just experimentation environments
- Experience designing and improving prompt-based systems to achieve reliable, high-quality outcomes
- Strong experience with agentic workflows, tool-using AI systems, or multi-step AI orchestration
- Experience building evals, regression tests, benchmarks, and monitoring for AI workflows
- Strong understanding of tradeoffs in model quality, latency, cost, reliability, and system design
- Strong scripting or coding ability in languages such as Python, Go, or TypeScript
- Comfort working with APIs, backend systems, data flows, and cloud environments
- Strong written and verbal communication skills
Preferred Qualifications
- Experience supporting fast-moving startup engineering teams
- Experience building products from 0 to 1
- Experience with fine-tuning LLMs, synthetic dataset creation, or benchmark development
- Experience working with sensitive or regulated data domains such as tax, accounting, finance, legal, or healthcare
- Familiarity with modern AI evaluation and observability tooling
How We Define Success in This Role
A strong Senior AI Engineer in this role:
- Ships AI features that create real user value
- Improves automation, accuracy, and reliability across important workflows
- Operates with high autonomy and strong product judgment
- Moves quickly without sacrificing reliability or sound engineering practices
- Helps the team make better decisions about how to build and evaluate AI systems
Stack Context
TaxGPT's core stack: Django, FastAPI, React / Next.js, Go, AWS EKS. Recent expansion into Azure and GCP. Kubernetes via Porter for deployment. PostgreSQL. GitHub for source control.
Why Join Us
This is an opportunity to help define the AI systems at the core of TaxGPT’s product experience. You will have meaningful ownership, deep technical scope, and the chance to shape how AI is built, evaluated, and shipped across the company.
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