AI Technical Lead

Crowe•Chicago, IL

4d•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. The role follows a forward deployed engineer model: the technical lead partners directly with Audit practitioners and subject matter experts, learns their workflows firsthand, designs solutions while building them, and owns delivery outcomes end to end. The position 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 managing the scope, timelines, stakeholder communication, and technical decisions for assigned agents. It includes building reusable engineering practices, CI/CD and evaluation capabilities, production monitoring and observability, and—when the portfolio grows—leading a small team of forward deployed engineers. The lead also makes product decisions with Audit SMEs, defines and tracks business-impact KPIs, and communicates technical recommendations to both engineering teams and business leaders.

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 end to end in a fast-paced, cross-functional environment, with proactive independent problem-solving.
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 major cloud platforms (AWS, Azure, and/or GCP), including managed AI services, cloud-native integration patterns, scalable data architectures, and secure enterprise deployments.
Experience with Azure DevOps, including building and maintaining 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 leaders and translating complex requirements into practical technical solutions.

Nice To Haves

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent professional 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, or Microsoft Copilot Studio.
Knowledge of retrieval-augmented generation (RAG), 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 development standards, reusable patterns, and practices for a growing team and portfolio of production solutions.
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 build workflow software without a separate product-owner layer.
A demonstrated interest in 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, and technical papers.
Azure experience.

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 SMEs 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 project 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 wider Audit technology ecosystem.
Implement and maintain production monitoring, observability, alerting, and 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 in advancing the roadmap for Audit stakeholders.
Develop and evolve 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, sharing reusable patterns and avoiding duplicated effort.
Define and track KPIs, assess ROI and business cases, and make product decisions directly with subject matter experts.
Proactively identify solutions, use data and insights to shape recommendations, and follow initiatives through to completion.
Communicate complex technical ideas, strategies, and recommendations effectively to technical staff and business leaders.