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Senior AI Engineer
Location: Remote
About the Role

Deduction is looking for a Senior AI Engineer to join its growing AI team and work closely with the Founding AI Engineer.

This is an applied AI engineering role, not a purely research-oriented position. You will help expand, harden, and scale Deduction's agentic AI systems while building the production infrastructure required to make AI reliable, observable, secure, and scalable.

You will operate at the intersection of AI platform engineering, production backend engineering, and full-stack product development.

The ideal candidate is a strong builder who enjoys solving ambiguous problems and turning emerging AI capabilities into reliable production systems—particularly in environments where accuracy, security, privacy, and compliance are critical.

Key Responsibilities

Architect & Scale AI Systems

• Partner closely with the Founding AI Engineer to evolve Deduction's AI architecture.
• Build robust, scalable, and governed AI systems for production use.
• Help establish engineering standards and architectural patterns for the company's AI platform.

Context Engineering & AI Reasoning

• Design sophisticated context-engineering systems for AI agents.
• Manage memory, state, context windows, and information retrieval.
• Improve AI reliability, performance, and overall user experience.
• Develop mechanisms that enable AI systems to reason effectively through complex tax workflows.

AI Evaluation & Observability

• Build a multi-layered evaluation platform for continuous AI quality improvement.
• Develop comprehensive offline test suites and evaluation frameworks.
• Implement LLM-as-a-judge systems, including AI-assisted auditing.
• Incorporate production feedback and CPA moderation into evaluation workflows.
• Build a continuous data flywheel to improve model and agent performance.

Full-Stack AI Development

• Build and ship production AI features using TypeScript and Node.js.
• Integrate AI capabilities directly into Deduction's core product.
• Work across backend, AI infrastructure, and product experiences.
• Contribute to text engineering and AI-driven UI/UX experiences.

Security, Privacy & Compliance

• Design secure context boundaries and data-retrieval pathways.
• Ensure AI systems enforce appropriate security and privacy controls.
• Build systems capable of operating reliably in a highly regulated environment.
• Protect sensitive customer and financial information throughout the AI workflow.

AI-Native Engineering

• Use modern AI coding assistants and AI development tools to accelerate engineering.
• Establish best practices for AI-assisted software development.
• Develop automated testing and development workflows that maintain quality while increasing engineering velocity.
• Help the broader engineering team adopt effective AI-native development practices.

Required Qualifications

Education

• Bachelor's or advanced degree in Computer Science or a related STEM field, such as:
• • Engineering
  • Mathematics
  • Physics
  • Computer Science

Professional Experience

• 6–10 years of software engineering experience, with significant experience in applied AI/LLM systems.
• Strong full-stack or backend engineering background.
• Professional experience primarily using TypeScript and/or Python.
• Demonstrated experience taking AI systems from concept/prototype to production.
• Experience working in an early-stage startup, preferably in a 0→1 environment.
• Strong ability to critically evaluate AI models, tools, architectures, and emerging AI trends.

Technical Skills

• Applied AI / LLM engineering
• AI orchestration
• Context engineering
• AI agent development
• Evaluation and observability systems
• Production backend engineering
• Data pipelines and infrastructure
• TypeScript / Node.js
• Python
• AI-assisted development and coding tools

Preferred Qualifications

• Experience in fintech or another highly regulated industry.
• Experience with document processing, document intelligence, or parsing complex information.
• Experience structuring and extracting information from unstructured data.
• Experience building systems that process information from multiple sources.
• Experience working across both startup environments and high-performing engineering organizations.
• Experience at companies such as Amazon, Meta, Stripe, or similarly engineering-intensive organizations.
• Experience building AI systems where reliability, security, and observability are critical.

Ideal Candidate Profile

The ideal candidate combines strong software engineering fundamentals with practical AI expertise.

You should be someone who:

• Has successfully shipped AI-powered products to production.
• Enjoys working in ambiguous, fast-moving startup environments.
• Can balance research awareness with practical engineering judgment.
• Understands both the capabilities and limitations of modern AI/LLM systems.
• Is comfortable building greenfield systems from the ground up.
• Can evaluate AI outputs critically rather than simply relying on model performance claims.
• Uses AI development tools effectively to increase engineering velocity.
• Has demonstrated an exceptional quality, whether through education, a side project, technical achievement, entrepreneurial work, or an exceptional professional accomplishment.

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