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

Alvarez & Marsal; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Alvarez & Marsal in India is seeking an experienced GenAI & Data Solution Architect to own enterprise‑scale AI systems, from data ingestion to production deployment. You will lead end‑to‑end AI strategy, architecture, governance, and roadmaps, collaborating with cloud platforms (Azure/AWS/GCP), MLOps, and responsible AI initiatives.

Strong leadership and stakeholder communication are essential to scale enterprise AI programs.

Qualifications

• 9‑14 years of AI/ML and data platforms experience with GenAI/LLM‑based systems
• Advanced degree (Master’s or Ph.D.) in AI, Data Science, CS or related field
• Strong expertise in ML, DL, NLP, and generative models
• Hands‑on Python with frameworks such as PyTorch, TensorFlow, Hugging Face, scikit‑learn, LangChain
• Experience deploying AI solutions on Azure, AWS or GCP (Azure ML, SageMaker, Vertex AI) and Kubernetes
• Strong MLOps/LLMOps knowledge, APIs, and cloud‑native architectures
• Proven delivery of AI‑powered SaaS or internal platforms
• Business acumen to align AI strategy with enterprise goals
• Ability to lead stakeholders, mentor engineers and collaborate cross‑functionally
• Excellent problem‑solving, communication and leadership in evolving AI landscape

Responsibilities

• Own end‑to‑end AI and data architecture (ingestion, feature engineering, model layers, orchestration, UI)
• Define reference architectures for GenAI, predictive ML, and hybrid AI systems
• Ensure alignment with ERP, Data Lakes and IAM
• Design and govern AI operating models (MLOps/LLMOps) and CI/CD pipelines
• Build production‑grade AI microservices and APIs using Python, Flask, FastAPI, Docker, Kubernetes
• Lead Responsible AI initiatives addressing ethics, privacy, transparency and regulatory compliance
• Communicate complex AI concepts to technical and non‑technical stakeholders
• Architect and govern scalable agent frameworks and event‑driven orchestration patterns
• Coordinate technical planning across delivery sprints, vendor integrations, and product releases
• Define evaluation frameworks for accuracy, relevance, bias, explainability and robustness

Skills

Generative AI

LLMs

Python

ML frameworks

Cloud platforms

MLOps/LLMOps

Leadership & Stakeholder

Education

Master’s or Ph.D. in AI/CS

Tools

Kubernetes

Docker

LangChain

HuggingFace

SageMaker

Job description

About Alvarez & Marsal

Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action‑oriented professionals in more than 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. Guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity, we foster a collaborative environment and engaging work.

The Team

• 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, and transformation excellence for digital transformation
• Data & AI services – Help clients harness 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.
• Requirements: 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 seek an innovator with deep expertise in Generative AI, large language models (LLMs), and cloud‑based AI platforms (Azure, AWS, or GCP). The candidate should thrive in a fast‑paced, dynamic consulting environment, lead teams, and build 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 systems
• 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 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 your personal journey. Our people highlight the growth opportunities, 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.