AI Technical Lead

Crowe•Tampa, FL

1d•$102,400 - $204,100•Hybrid

About The Position

Crowe’s Studio team is seeking a hands-on technical leader to design, develop, and manage the lifecycle of AI agents that accelerate delivery of Crowe’s Audit services. Working within Crowe’s forward deployed engineer model, the AI Technical Lead partners directly with Audit practitioners and subject matter experts, learns workflows firsthand, and designs and builds solutions alongside them. The role owns agent outcomes end to end and establishes technical patterns, a Skills-based architecture, and engineering practices for a growing portfolio of agents. The role remains hands-on in Python development while balancing project scope, timelines, prioritization, stakeholder communication, and technical decision-making. It includes building production monitoring and observability, agent evaluation approaches, and Azure DevOps CI/CD pipelines. As the portfolio expands, the position is expected to grow into leading a small team of forward deployed engineers, mentoring team members, and helping scale the engineering capability.

Requirements

At least 8 years of professional software engineering experience developing, implementing, and supporting enterprise applications and services.
At least 5 years of professional Python development experience building enterprise-grade applications and services.
Ability to write clean, maintainable, modular, testable, well-structured Python code designed for long-term support and scalability.
At least 1 year of hands-on experience designing, developing, and productionizing AI agents or AI-assisted workflows using a major AI platform or model provider such as Microsoft, Anthropic, or OpenAI.
Hands-on experience developing agents with a Skills-based architecture, including authoring and maintaining Skills definitions, markdown-based instructions, supporting resources, and executable code.
Experience testing and evaluating AI systems, including automated evaluators, representative test cases, regression testing, and analysis of agent failure modes.
Ability to embrace and advocate for AI-assisted software engineering, including coding assistants, automated testing, and design-time AI tools.
Project management experience scoping, planning, and managing technical projects or initiatives end to end in a fast-paced, cross-functional environment.
Proactive, independent problem-solving skills.
Experience providing technical leadership to software engineering teams, including mentoring, 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 patterns, scalable data architectures, and secure enterprise-grade deployments.
Experience with Azure DevOps CI/CD pipelines or a similar platform, and Git-based version control.
Excellent verbal and written communication skills, including explaining complex technical work to non-technical business leaders and translating requirements into practical technical solutions with product managers, architects, and business stakeholders.

Nice To Haves

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent professional experience.
Azure experience.
Experience developing software or AI solutions for Audit, accounting, public accounting, financial services, or another regulated industry.
Proficiency with modern AI/ML frameworks, tools, and agent platforms such as MCP, A2A, Microsoft Foundry, OpenAI Agent SDK, Microsoft Agent Framework, Claude SDK, LangGraph, LangChain, LlamaIndex, Microsoft Copilot Studio, or equivalent.
Knowledge of retrieval-augmented generation, vector databases, embeddings, and techniques for grounding model outputs in enterprise data.
Experience delivering solutions with the Microsoft .NET stack, C#, and SQL Server.
Experience establishing or scaling an engineering capability, including defining development standards, reusable patterns, and practices for a growing team and production portfolio.
Consulting, product management, investment banking, or startup experience that has developed commercial and product instincts.
Prior experience as a forward deployed engineer or in a similar embedded technical role, partnering directly with subject matter experts to design and build workflow software without a separate product-owner layer.
Passion for sharing knowledge through cross-training, internal talks, or detailed ticket comments.
Curiosity and a continuous-learning mindset in generative AI and applied machine learning, including interest in emerging models, architectures, techniques, research, technical papers, and pre-release concepts.

Responsibilities

Design, develop, maintain, and continuously improve AI agents and agent-assisted workflows for common tasks across Crowe’s Audit practice.
Work directly with Audit subject matter experts and practitioners to understand workflows and build agents alongside them.
Write, review, test, and maintain Python codebases, Skills, instructions, prompts, and supporting agent resources.
Manage scope, timelines, stakeholder communication, planning, prioritization, and coordination for owned agents.
Design agents using a Skills-based architecture with modular, reusable capabilities.
Serve as the technical authority for the agent layer and partner with architects and engineering teams to align with the broader Audit technology ecosystem.
Implement and maintain production monitoring, observability, and alerting, including trace-level visibility into agent reasoning and tool calls.
Establish reusable engineering patterns and practices for developing, evaluating, deploying, supporting, and enhancing agents.
Build and maintain Azure DevOps CI/CD pipelines to automate agent testing, evaluation, and deployment across environments.
As the portfolio grows, lead a small team of forward deployed engineers advancing the roadmap for Audit stakeholders.
Help develop agent evaluation strategies, including representative test cases, automated evaluators, regression testing, accuracy metrics, and processes for identifying and addressing behavior changes.
Mentor engineers and provide technical leadership through code and design reviews.
Promote collaboration across the Audit business unit and Studio to surface opportunities, share reusable patterns, and avoid duplicated work.
Define and track KPIs, assess ROI and business cases, and communicate business impact; make product decisions alongside subject matter experts.
Identify solutions proactively, take initiative, and follow through to completion.
Use data and insights to shape and defend recommendations aligned with Audit’s business needs.
Communicate technical ideas, strategies, and recommendations effectively to technical staff and business leaders.