Senior Manager AI Solutions Architecture

The Team:

Our Business Applications and Analytics team plays a pivotal role in driving business success through data-driven decision-making and operational excellence. This dynamic team manages enterprise-wide applications, including ERP, CRM, and BI systems. By harnessing the power of data and advanced analytical tools, we provide valuable insights that inform strategic initiatives, optimize processes, and enhance overall performance.

Within this team sits our AI Solutions group, a small, high-impact squad of AI Solutions Architects partnering with AI Solutions Engineers building and scaling internal AI/GenAI capabilities across the company. This is the team you will lead.

Position Overview:  

Diligent is ‘All-In’ on AI and is seeking an experienced, hands-on leader to head our AI Solutions Architecture function as a Senior Manager / Director. You will lead a team of six, a mix of AI Solutions Architects and AI Solutions Engineers, responsible for identifying, designing, building, and scaling AI/GenAI solutions that accelerate our internal AI capabilities across Marketing, GTM/Sales, Customer Success & Support, Finance, HR, Legal, and Product & Engineering.

This is both a people-leadership and a technically heavy role with expectation to get your hands dirty. You will own the strategy, roadmap, and delivery of the internal AI portfolio: setting technical direction and architectural standards, coaching and growing the team, partnering with senior business stakeholders to prioritize the highest-value opportunities, support execution, and ensuring every solution is delivered securely, responsibly, and with measurable ROI. The ideal candidate pairs strong AI/GenAI and enterprise-systems fluency with a track record of building and leading high-performing engineering or solutions teams, and can move comfortably between executive conversations and technical delivery.

Alongside the internal AI portfolio, this role required to partner with platform engineering for a number of Diligent’s core IT platforms including Salesforce, Gainsight, Atlassian, Snowflake, Workday, Netsuite and the Microsoft ecosystems taking accountability for their continued modernization and for embedding AI capability into them where it drives value.

The ideal candidate pairs strong AI/GenAI and enterprise-systems fluency with a genuine builder’s track record and experience leading high-performing engineering or solutions teams, and can move comfortably between executive conversations, deep technical review, and hands-on delivery.

Key Responsibilities:

Leadership & Team Development

• • Lead, coach, and grow a team of five AI Solutions Architects and Engineers — setting clear goals, providing regular feedback, and supporting career development and technical growth.
  • Own hiring and capability planning for the function: attract, retain, and develop top AI/engineering talent, and shape the team structure as the portfolio scales.
  • Foster a culture of experimentation, rapid iteration, engineering excellence, and responsible AI, where the team learns fast and shares findings openly.
  • Balance leadership with hands-on depth stay technically credible enough to review designs, unblock the team, and make sound architectural trade-off decisions.

Strategy & Roadmap

• • Define and communicate the strategy, vision, and roadmap for internal AI solutions, aligned to Diligent’s business goals and operating priorities.
  • Partner with senior business leaders across Marketing, GTM/Sales, Customer Success & Support, Finance, HR, Legal, and Product & Engineering to identify, prioritize, and act on the highest-value AI opportunities.
  • Develop and steward architectural standards, reusable patterns, and reference implementations that the Architects design and the Engineers build against, ensuring consistency and reuse across the portfolio.
  • Manage the portfolio and its trade-offs — sequencing initiatives, allocating team capacity, and balancing quick wins against durable, scalable platform investments.

Delivery & Technical

• • Operate as a player-coach actively contribute to hands-on build work (prototypes, reference implementations, integrations, and unblocking complex problems), adding real delivery capacity to the team rather than managing from a distance.
  • Oversee the end-to-end lifecycle of AI solutions from ideation and prototyping through production deployment, monitoring, tuning, and operational handover.
  • Ensure solutions embed AI/GenAI capabilities (RAG, copilots, agents, summarization, classification) into core business applications such as ERP, CRM, and BI in a robust, maintainable, and user-friendly way.
  • Champion quality and reliability driving standards for architecture reviews, testing, observability, cost management, and incident response across the team’s work.
  • Establish and track KPIs and ROI for AI initiatives, monitoring the performance and effectiveness of deployed solutions and continually refining them.

Governance, Responsible AI & Stakeholder Management

• • Champion responsible AI privacy, security, fairness, and ethical guidelines — and ensure compliance with data protection and regulatory requirements across all implementations.
  • Act as the primary point of contact and trusted advisor to business and executive stakeholders on internal AI capability, translating technical possibilities into clear business value.
  • Drive AI and data literacy across the organization through enablement, workshops, and reusable documentation, runbooks, and playbooks.
  • Stay abreast of AI advances — tools, patterns, and methodologies — and introduce the right ones to the organization at the right time.

Required Qualifications:

• Bachelor’s degree in Computer Science, Engineering, AI/ML, Data Science, or a related field (or equivalent experience); an advanced degree is a plus.
• 8+ years in software, data, or solutions engineering, including experience building and operating production AI/GenAI or enterprise systems.
• 3+ years of people leadership managing and developing engineers, architects, or technical solutions professionals, ideally including hiring and performance management.
• Proven track record of setting technical direction and delivering enterprise-scale AI/GenAI or software solutions with measurable business impact.
• Strong, current understanding of AI/GenAI patterns LLMs, prompt engineering, RAG, agents/workflows, and output evaluation and the judgment to apply them appropriately.
• A genuine builder who leads from the front (player-coach): still writes code and delivers hands-on, with proficiency in at least one modern language (e.g., Python, TypeScript/Node.js, Java, or C#), APIs and integrations, and cloud platforms (AWS preferred; Azure/GCP welcome).
• Experience owning or engineering enterprise IT platforms the Atlassian suite, the Microsoft ecosystem (M365 / Azure), or comparable including configuration, integration, automation, and lifecycle management.
• Experience integrating AI/GenAI into enterprise systems such as Salesforce/CRM, ERP, or BI/analytics platforms.
• Strong grasp of responsible AI, privacy, security, and compliance in a regulated or enterprise SaaS context.
• Excellent communication and stakeholder-management skills able to influence senior business leaders and explain technical trade-offs to non-technical audiences.
• Experience leading cross-functional, globally distributed teams across business, data, security, and operations.

Preferred Qualifications:

• Experience standing up or scaling an internal AI / AI enablement function within a global SaaS or enterprise organization.
• Familiarity with MLOps/LLMOps concepts, model lifecycle, experiment tracking, evaluation, and drift monitoring, and with containerization and CI/CD.
• Exposure to classical ML/analytics (e.g., Scikit-learn, dashboards) sufficient to guide and collaborate with data and ML teams.
• Prior experience in a global SaaS company operating across India, North America, and EMEA time zones.
• Strategic thinker with strong analytical and problem-solving skills and a demonstrated ability to drive measurable outcomes through AI/GenAI.