AI Technical Lead

Location: Hybrid; available in 38 locations. Candidates must verify eligibility to work in the United States. Visa sponsorship is not available.

Salary: $102,400–$204,100 per year, subject to geographic differentials and experience.

Company

hirify.global provides audit, tax, advisory, consulting, and other professional services through hirify.global LLP and hirify.global Advisory LLC, with AI initiatives supporting its audit and business services.

What you will do

• Design, develop, maintain, and continuously improve AI agents and agent-assisted workflows that accelerate common Audit tasks.
• Work directly with Audit subject-matter experts as a forward deployed engineer to understand workflows and build solutions alongside practitioners.
• Write, review, test, and maintain substantial Python codebases, Skills definitions, instructions, prompts, and supporting agent resources.
• Own technical delivery, including scope, timelines, stakeholder communication, architecture decisions, and alignment with the broader Audit technology ecosystem.
• Implement production monitoring, observability, alerting, trace-level visibility, evaluation strategies, regression testing, and accuracy metrics.
• Build Azure DevOps CI/CD pipelines, establish reusable engineering practices, mentor engineers, and eventually lead a small forward deployed engineering team.

Requirements

• 8+ years of professional software engineering experience developing, implementing, and supporting enterprise applications and services.
• 5+ years of professional Python development experience building enterprise-grade applications and services, with clean, maintainable, modular, testable, well-structured, production-grade code.
• 1+ years of hands-on experience designing, developing, and productionizing AI agents or AI-assisted workflows using a major provider or platform such as Microsoft, Anthropic, or OpenAI.
• Hands-on experience developing agents with a Skills-based architecture, including Skills definitions, markdown-based instructions, supporting resources, and executable code.
• Experience testing and evaluating AI systems through automated evaluators, representative test cases, regression testing, and analysis of agent failure modes.
• Experience using AI-assisted software engineering practices, including coding assistants, automated testing, and design-time AI tools.
• Project management experience scoping, planning, and managing technical initiatives end to end in a fast-paced, cross-functional environment, with proactive and independent problem-solving.
• Technical leadership experience, including mentoring engineers, conducting code and design reviews, and establishing engineering practices and standards.
• Experience designing and deploying AI/ML solutions on AWS, Azure, and/or GCP, including managed AI services, cloud-native integration, scalable data architectures, and secure enterprise deployments.
• Experience with Azure DevOps, CI/CD pipelines, and Git-based version control, plus strong verbal and written communication with technical and non-technical stakeholders.

Nice to have

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent professional experience.
• Experience in audit, accounting, public accounting, financial services, or another regulated industry.
• Experience with MCP, A2A, Microsoft Foundry, OpenAI Agent SDK, Microsoft Agent Framework, Claude SDK, LangGraph, LangChain, LlamaIndex, Microsoft Copilot Studio, RAG, vector databases, embeddings, and enterprise-data grounding.
• Experience with Microsoft .NET, C#, and SQL Server.
• Experience scaling engineering capabilities, defining development standards, and creating reusable patterns for production solution portfolios.
• Consulting, product management, investment banking, startup, forward deployed engineering, or similar embedded technical experience.
• Experience sharing knowledge through cross-training, internal talks, or detailed technical documentation.
• Curiosity and continuous learning in generative AI and applied machine learning, including emerging models, architectures, technical papers, and pre-release concepts.

Culture & Benefits

• Hybrid work environment with flexibility to balance work and personal commitments.
• Values centered on Care, Trust, Courage, Stewardship, ethics, and integrity.
• Comprehensive employee total rewards and benefits package.
• Inclusive culture with equitable access to career growth and leadership opportunities.
• Career coaching and ongoing professional development support.