Systems Engineer, AI Platforms - Global Capability Center

Alvarez & Marsal; Gurugram District; On-site; INR 4,500,000 - 6,000,000; Full time

Job summary

Alvarez & Marsal in India is seeking a Systems Engineer to lead the Enterprise AI tools strategy and operations within GAIKO. You will shape the tech direction, manage platforms like Claude, ChatGPT, and Cursor, and govern APIs and MCP integrations at scale.

You will collaborate with Architecture, IT, Security, Risk, and Legal to ensure secure, compliant deployment, provide reliable service, and drive adoption of enterprise AI capabilities across the firm.

Qualifications

• 8–10+ years in systems engineering or SaaS admin roles.
• Hands-on experience with enterprise AI platforms.
• Experience with REST APIs, MCP, and security controls.
• Ability to evaluate and govern AI tool deployments.
• Strong communication across product, security, IT teams.

Responsibilities

• Manage and administer AI platforms (Claude, ChatGPT, Cursor) and guardrails.
• Define and evolve enterprise API offering and access control.
• Enable MCP connections and connectors with governance.
• Lead technical evaluations and risk assessments for tools.
• Collaborate with product, architecture, security, and legal teams.

Skills

Enterprise AI platforms

REST APIs & webhooks

Security & risk management

SaaS platform administration

API governance

Education

Bachelor's in CS/ENG

Tools

Claude

ChatGPT

Cursor

MCP wrappers

Job description

Description

About Alvarez & Marsal

Alvarez & Marsal (A&M) is a global consulting firm with entrepreneurial, action and results-oriented professionals. 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

You will join the Global AI & Knowledge Organization (GAIKO), which leads A&M’s AI strategy, enablement, and knowledge infrastructure. Within GAIKO’s AI & Data organization, the AI Tools team manages the enterprise AI platforms practitioners use in their daily work. The team brings together business needs, vendor capabilities, and firm requirements to evaluate, introduce, and continually improve AI tools for thousands of global practitioners.

How you will contribute

As a Systems Engineer, you will provide technical direction and oversight for A&M’s Enterprise AI tools offering. You will help shape the technology strategy, manage and evolve existing platforms, evaluate new AI capabilities, oversee the enterprise API offering, and govern the MCP integrations and connectors that extend the core platforms.

This hands-on role requires strong technical expertise in Enterprise AI and SaaS platform management, APIs, Model Context Protocol (MCP) integrations, and the governance and controls needed to operate these capabilities securely at scale. You will assess capabilities from a technical standpoint, configure approved services, implement appropriate guardrails, and support reliable operation at scale.

You will work closely with the Product and colleagues across Architecture & Engineering, Enterprise IT, Security, Risk, and Legal to take capabilities from technical evaluation through pilot, deployment, and ongoing operation

1. Manage Existing AI Platforms

• Platform administration: Own configuration and administration of approved platforms such as Claude, ChatGPT, and Cursor, including workspaces, feature settings, provisioning, groups, roles, and permissions; automate recurring administrative tasks.
• Capability evaluation: Define and apply technical evaluation criteria for new models, features, and agents within approved platforms, documenting capabilities, performance, and limitations to inform adoption decisions.
• Controls and governance: Identify security and risk control gaps, recommend guardrails, and work with compliance teams (security, risk, legal) to review risks and implement agreed controls for safely rollout capabilities
• Deployment management: Manage the deployment lifecycle for approved capabilities and configuration changes, including approval gates, controlled pilots, phased rollout, post-launch validation, and rollback procedures.
• Service operations: Maintain platform health, operational documentation, and support arrangements; coordinate incident resolution and vendor escalations.

2. Manage the Enterprise API Offering

• Offering management: Define and evolve the enterprise API offering, including supported services, technical configurations, service standards, and support requirements
• Access governance: Provision and govern access for approved teams and applications, managing accounts, projects, service identities, model permissions, credential lifecycles, and access ownership.
• Consumption management: Configure available usage limits, budgets, and alerts; monitor consumption and spend and recommend adjustments.
• Service operations: Support API consumers with onboarding, documentation, and troubleshooting; manage service reliability and coordinate responses to vendor changes, deprecations, and incidents.

3. Manage MCPs and Connectors

• Integration enablement: Assess and enable MCP connections and native connectors between core AI platforms and enterprise applications, data, and services, including the use of approved MCP wrappers for existing APIs.
• Connection governance: Configure and validate authentication, tool permissions, data boundaries, and permitted actions; conduct access reviews and maintain ownership, dependency, and configuration records.
• Lifecycle and operations: Manage connection health, changes, and support issues; assess capacity and scaling requirements and coordinate improvements or retirement.

4. Evaluate New AI Tools

• Evaluation framework: Establish reusable technical frameworks for assessing AI tools and capabilities, defining evaluation criteria, test scenarios, evidence requirements, and decision gates.
• Technical evaluation: Run hands-on security and risk assessments of candidate tools, models, and agents for technical fit and enterprise readiness, including performance, integration requirements, scalability, and supportability; document capabilities, limitations, and gaps.
• Risk and control assessment: Work with Architecture, Security, and other stakeholders to assess technical risks, identify control gaps, and agree requirements for enterprise approval.
• Adoption recommendation: Recommend whether and how to introduce new offerings, documenting the rationale, deployment options, dependencies, implementation effort, and operational requirements.

Qualifications

• (At least 8-10+ yearsof relevant professional experience in systems engineering, SaaS administration, Enterprise AI platform management, or a related discipline.
• Hands-on experience managing Enterprise AI platforms such as Claude, ChatGPT, and Cursor, including configuration, access management, platform controls, and production support.
• Strong understanding of LLM platform capabilities, including models, features, and agents.
• Advanced knowledge of AI workflow design, security, and risk management
• Experience defining and applying technical evaluation criteria, with strong judgment in assessing architectural fit, performance, integration dependencies, controls, scalability, and deployment options.
• Strong working knowledge of REST APIs and webhook integrations, including authentication, service identities, credential management, usage limits, consumption monitoring, and troubleshooting.
• Strong hands-on knowledge of MCP, including client-server interactions, tool discovery and invocation, authentication, permission scopes, and how existing APIs can be exposed through MCP wrappers.
• Working knowledge of enterprise identity and access management, including SSO, SAML or OpenID Connect, SCIM provisioning, and role-based access controls.
• Ability to use administrative consoles, logs, API testing tools, and lightweight scripts in Python, PowerShell, JavaScript/TypeScript, or a comparable language for diagnostics and operational automation.
• Experience managing SaaS service lifecycles, including controlled pilots, release testing, deployment, change management, monitoring, incident resolution, vendor escalation, and retirement.
• Strong troubleshooting and communication skills, with the ability to explain technical findings, communicate controls and guardrails, document operational procedures, and work effectively across product, engineering, IT, and security teams.
• Experience supporting MCP services at enterprise scale, including hosted service dependencies, capacity planning, and operational efficiency
• Familiarity with Microsoft Entra ID, Microsoft Graph, Microsoft 365 integrations, or Power Automate.
• Experience with risk monitoring and enterprise controls such as data loss prevention, audit logging, retention, and access reviews.
• Experience in consulting, professional services, or another environment with complex client-data requirements.

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.