Manager, Applied AI Engineer

As an Applied AI Engineer Manager at Alvarez and Marsal, you will lead end-to-end delivery of production-grade AI solutions that turn everyday consulting workflows into scalable headless skills and agentic systems. This role partners with business leaders, Knowledge Management and Data, and multiple engineering teams to build, deploy, monitor, and iteratively improve applied AI capabilities.

Onsite Location

Nashville, TN (onsite)

Compensation

USD 140,000 - 180,000 per year

Role Summary

The Manager, Applied AI Engineer at Alvarez & Marsal (A&M) guides technical direction and mentoring across a pod while owning the delivery lifecycle from proof of concept through production. The position includes designing and building headless skills and agents, coordinating requirements with internal teams, and ensuring reliable operation of AI systems deployed into consulting work.

Key Responsibilities

• Own end-to-end delivery of applied AI solutions, including problem framing, build, deployment, monitoring, and iteration from proof of concept to production.
• Partner with business unit leaders to understand their workflows, translate needs into skills and agents, and align on clear success metrics.
• Coordinate with Knowledge Management and Data team leads to gather and clarify requirements, translating them into skill and agent designs.
• Partner with Data Engineering, BIU, and Intelligence Layer teams to ensure solutions use reliable, production-grade data.
• Design, build, and operate headless skills and agentic workflows, including multi-step orchestration, tool routing, retrieval, guardrails, evaluation, and human-in-the-loop controls.
• Build and maintain automated skill-building pipelines, including templates, scaffolding, testing and evaluation harnesses, packaging, and deployment to enable consistent and rapid releases.
• Create integrations with large language model platforms and use the Model Context Protocol (MCP) to make skills available to approved AI tools and the Intelligence Layer.
• Integrate structured and unstructured enterprise content while preserving source permissions, metadata, and governance requirements.
• Guide the team in assessing current Power Platform and wider Microsoft stack processes and reimagining them as AI-first workflows, converting them into skills and agents or connecting them to skills and agents.
• Train the wider team through workshops, playbooks, templates, worked examples, and office hours focused on building skills.
• Mentor engineers through pairing, code and design reviews, and hands-on coaching to raise the quality bar for skills and agents across the pod.
• Apply and help shape engineering standards for skills and agents in collaboration with the Intelligence Layer tech lead, including evaluation, CI/CD, versioning, reproducibility, and performance monitoring.
• Advise on tools, frameworks, and design patterns, with technical decisions made by the Intelligence Layer tech lead together with the Intelligence Layer lead.
• Support responsible AI practices, including data privacy, client confidentiality, model risk, and decisions about third-party models.
• Communicate results, tradeoffs, risks, and blockers clearly to pod leadership, the Intelligence Layer tech lead, business unit leaders, and senior stakeholders in business terms.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience
• 5+ years in software engineering, data science, machine learning, or applied AI engineering, including 2+ years building and shipping LLM or agent-based systems in production
• Strong hands-on Python development experience
• Experience building LLM and generative AI applications, including RAG, prompting, evaluation, and agentic patterns
• Demonstrated track record of designing, building, and shipping multiple AI agents and skills into production (examples or a portfolio discussed at interview)
• Experience building automated pipelines for creating, testing, evaluating, and deploying skills or agents at scale
• Hands-on experience with MCP, agent frameworks (for example, Claude Agent SDK, LangGraph, Semantic Kernel, or similar), and reusable skill design
• Experience with CI/CD, testing, and observability for production systems
• Excellent communicator who can explain technical concepts in plain business language and conduct discovery sessions with business unit leaders
• Proven mentor and teacher who has upskilled other engineers or non-technical colleagues and enjoys building capability in others
• Confident presenting to and facilitating workshops with senior stakeholders
• Collaborative team player who builds strong working relationships across teams
• Bias toward action, including shipping often and learning through iteration
• High ownership and comfort with ambiguity and shifting priorities
• Sound judgment on when to ship, when to iterate, and when to stop

Technologies

Python, LLM, agent-based systems, RAG, Model Context Protocol (MCP), Claude Agent SDK, LangGraph, Semantic Kernel, CI/CD, Power Platform, SharePoint, Power BI, Azure, Power Automate, Power Apps, Fabric, SQL, Microsoft tools (SharePoint, Power Platform, Power BI)

Team and Mission

The AI Lab Team sits within A&M's Global AI & Knowledge Organization (GAIKO). GAIKO brings together the firm's AI and Knowledge Management capabilities to put trusted, governed AI into everyday consulting work. The Lab's mission is to turn repeatable business workflows into scalable agents and AI skills.

Benefits

• Healthcare plans
• Flexible spending and savings accounts
• Life, AD&D, and disability coverages
• 401(k) retirement savings plan
• Annual discretionary contribution to the 401(k), provided eligibility requirements are met
• Paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), ten federal holidays, and one floating holiday
• Parental leave

Nice to Have

• Experience with the Microsoft stack (SharePoint Online, Power Platform, Fabric/Power BI, Azure), including hands-on Power Automate and Power Apps experience, and the ability to re-engineer existing flows (strongly preferred)
• Experience with SQL and modern data platforms
• Experience working in Agile environments such as Scrum or Kanban
• Experience in a professional services or consulting environment

Your Journey at A&M

At A&M, professional growth is tied directly to performance, not tenure. Regular employees working 30 or more hours per week are also entitled to participate in Alvarez & Marsal Holdings' fringe benefits consisting of healthcare plans, flexible spending and savings accounts, life, AD&D, and disability coverages, as well as a 401(k) retirement savings plan. In addition, A&M offers a discretionary bonus program based on individual and firm performance. The salary range is $140,000 - $160,000 annually, dependent on variables including education, experience, skills, and geography.