Description

About Alvarez & Marsal

Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work—guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity - are why our people love working at A&M.

The Team

Our DTS team covers the full breadth of Technology Consulting and M&A services, including -

Technology M&A and Strategy - Assist clients to manage the technology aspects and business enablement of complex M&A, integrations and carve-outs as well as post-deal value creation
Technology Consulting - End to end technology advisory for clients, including developing technology roadmaps, platform/cloud/data advisory as well as transformation excellence for a digital transformation
Data & AI services - Helping clients in harnessing the power of data and cutting-edge analytics to drive intelligent decision-making and transform businesses
Develop GenAI and Agentic AI solutions that create real business value for clients through process re-invention

The Role

This role serves as the single-threaded technical owner for enterprise-scale AI and Generative AI solutions. The GenAI & Data Solution Architect is responsible for defining, designing, and governing end-to-end AI systems - from data ingestion and model orchestration to user experience and production deployment.
The role requires deep hands-on expertise in Generative AI, LLMs, RAG, agentic architectures, and cloud-native AI platforms, combined with strong architectural judgment to balance innovation, scalability, security, and cost.
We are seeking an innovator with deep expertise in Generative AI, large language models (LLMs), and cloud-based AI platforms (Azure, AWS, or GCP). The candidate should be comfortable working in a fast-paced, dynamic consulting environment, leading teams, experienced in building end-to-end AI strategy and roadmaps, ensuring customer success to scale enterprise-wide AI programs

How You Will Contribute

AI & Data Architecture
Own end-to-end AI and data architecture, including ingestion, feature engineering, model layers, orchestration, APIs, and UI integration
Define reference architectures for GenAI, predictive ML, and hybrid AI systems
Ensure alignment with enterprise platforms such as ERP, CMMS, Data Lakes, and IAM
Design and govern AI operating models (MLOps / LLMOps), standardizing model development, deployment, monitoring, and iteration
Establish CI/CD pipelines, monitoring, and retraining workflows using tools such as Azure DevOps, GitHub Actions, or AWS CodePipeline
Build production-grade AI microservices and APIs using Python, Flask, FastAPI, Docker, and Kubernetes
Continuously optimize AI systems for performance, scalability, reliability, and operational efficiency
Lead Responsible AI initiatives addressing ethics, bias, privacy, transparency, and regulatory compliance (e.g., EU AI Act)
Communicate complex AI concepts effectively to both technical and non-technical stakeholders
Generative AI Strategy & Agentic Systems
Architect and govern scalable, modular AI agent frameworks for enterprise reuse
Define event-driven orchestration and agentic execution patterns (e.g., LangGraph, Temporal, reflection-based workflows
Drive integration across GenAI platforms and internal frameworks to ensure consistency in observability, security, and governance
Develop reusable agent templates, blueprints, and context frameworks to accelerate onboarding of new use cases
Standardize GenAI design patterns including RAG, agentic workflows, tool calling, and memory/context management
Lead technical planning across delivery sprints, vendor integrations, and GenAI product releases
Design and build production-aligned PoCs and MVPs, ensuring smooth evolution into scalable enterprise solutions
Evaluate feasibility across business value, data readiness, performance, and cost
Decide optimal use of LLMs versus classical ML or deterministic logic based on use case requirements
Model Lifecycle, Quality, Cost & Risk Management
Optimize retrieval strategies, chunking, embeddings, grounding, and caching
Reduce hallucinations, latency, and token costs
Define evaluation frameworks covering accuracy, relevance, bias, explainability, and robustness
Establish prompt versioning, model versioning, retraining cadence, drift detection, and traceability across the AI lifecycle
Governance & Release Authority
Define non-functional requirements including SLAs, reliability, scalability, and cost controls
Act as the final technical authority for architecture decisions and production releases

Qualifications

9-14 years of experience in AI/ML and data platforms, with deep focus on enterprise GenAI and LLM-based system
Advanced degree (Master's or Ph.D.) in AI, Data Science, Computer Science, or a related field
Strong expertise in machine learning, deep learning, NLP, and generative models
Hands-on experience with Python and frameworks such as PyTorch, TensorFlow, Hugging Face, scikit-learn, LangChain, and agent frameworks
Experience building and deploying AI solutions on Azure, AWS, or GCP using services such as Azure ML, SageMaker, Vertex AI, and Kubernetes
Strong understanding of MLOps / LLMOps, APIs, and cloud-native architectures
Proven experience delivering AI-powered SaaS or internal platforms to automate workflows and enhance customer experience
Strong business acumen with the ability to align AI strategy with enterprise goals
Ability to engage senior stakeholders, lead cross-functional teams, and mentor AI engineers and data scientists
Excellent problem-solving, communication, and leadership skills, with adaptability to the rapidly evolving AI landscape

Your journey at A&M

We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person's unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career. We prioritize your well-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M. The possibilities are endless for high-performing and passionate professionals.

Associate Director, GenAI & Data Solution Architect - Global Capability Center