Manager, Applied AI Engineer

Alvarez and Marsal is building trusted, governed AI capabilities through its AI Lab team within the Global AI & Knowledge Organization (GAIKO). In this Manager role, you will lead end-to-end delivery of applied AI solutions, turning repeatable business workflows into production-ready headless skills and agentic systems used across the firm.

Based in New York, NY (onsite), you will partner closely with business, Knowledge Management and Data, and engineering groups to design reliable AI workflows, mentor teammates, and help shape engineering standards for skills and agents.

What You’ll Do

• Own delivery of applied AI solutions from proof of concept to production, including problem framing, building, deployment, monitoring, and iteration.
• Partner with business unit leaders to understand how teams work, translate needs into skills and agents, and align on clear success metrics.
• Work with Knowledge Management and Data team leads to gather and clarify requirements and translate them into skill and agent designs.
• Coordinate with Data Engineering, BIU, and Intelligence Layer teams to ensure solutions are grounded in 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, and packaging and deployment to enable consistent releases.
• Develop 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 Power Platform and wider Microsoft stack processes, reimagining them as AI-first workflows, and converting or connecting them to skills and agents.
• Train the broader team on building skills through workshops, playbooks, templates, worked examples, and office hours.
• Mentor engineers through pairing, code and design reviews, and hands-on coaching to raise quality 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.
• Surface recommendations on tools, frameworks, and design patterns, with technical decisions made by the Intelligence Layer tech lead alongside the Intelligence Layer lead.
• Support responsible AI use, including data privacy, client confidentiality, model risk, and decisions regarding third-party models.
• Communicate results, tradeoffs, risks, and blockers clearly to pod leadership, the Intelligence Layer tech lead, business unit leaders, and senior stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics or a related quantitative field (or equivalent practical experience)
• Cloud or AI-related certifications are a plus
• 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 designing, building, and shipping multiple AI agents and skills into production (examples or portfolio discussed in interview)
• Experience building automated pipelines for creating, testing, evaluating, and deploying skills or agents at scale
• Hands-on experience with MCP, agent frameworks (examples include Claude Agent SDK, LangGraph, Semantic Kernel, or similar), and reusable skill design
• Experience with CI/CD, testing, and observability for production systems
• Excellent communication skills, including explaining technical concepts in plain business language and facilitating discovery with business unit leaders
• Proven mentor and teacher, comfortable upskilling engineers or non-technical colleagues
• Confident presenting to and facilitating workshops with senior stakeholders
• Collaborative team player with strong relationships across teams
• Bias toward action, shipping through iteration, with comfort in ambiguity and shifting priorities
• Sound judgment on when to ship, iterate, or stop

Technologies

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

Compensation & Benefits

The salary range is USD 140,000 - 180,000 per year.

• Healthcare plans
• Flexible spending and savings accounts
• Life, AD&D, and disability coverages
• 401(k) retirement savings plan
• Annual discretionary contribution to their 401(k) retirement savings plan (if eligibility requirements are met)
• Paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), and ten federal holidays
• One floating holiday
• Parental leave
• Discretionary bonus program (based on factors including individual and firm performance)

Team Context

• 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 deliver trusted, governed AI in everyday consulting work.
• The lab’s mission is to turn repeatable business workflows into scalable agents and AI skills.
• Many workflows run today on Microsoft tools such as SharePoint, Power Platform, and Power BI, and are reworked into AI-first solutions reusable across the firm.
• Some solutions are built from scratch as internal teams bring new requests.