Senior Tech Lead

• Job Specification: AI Operations Lead ( Role: AIOps Lead)
• We are seeking an experienced and highly skilled AI Operations (AIOps) Lead to drive

Driving Agentic Automation and AIOps implementation, the operationalization, governance, monitoring, and continuous improvement of enterprise AI solutions .

This role requires a proven specialist capable of establishing scalable AI operating models while providing hands‑on leadership to ensure AI systems deliver reliable, secure, and measurable business outcomes.

Key Responsibilities & Requirements

• Provide expert leadership for the operational management and continuous improvement of AI, Machine Learning, and Generative AI solutions across the organization.

Driving Agentic Automation and AIOps implementation by providing oversight, resolving blockers and ensuring smooth execution.

Design the solution and implement, code review and lead the team - Google ADK (Agentic Framework), LLM - Google 2.0 Flash or 1.5, Lang graph.

Drive team to formalize the engineering and integration approaches (enterprise changes, impacts, and documentation standards).

Establish feasibility and checklist‑based transition / adoption approach with automated verifications where possible.

Formalize and package adoption standards for federated adoption of AI / Agentic interventions.

Run Training and Support Incidents/Escalations associated with Adoptions / Integrations.

For first time cases, establish / package all materials associated with ad.

• Develop and implement enterprise‑wide AIOps frameworks, operating models, standards, and best practices to ensure scalable and sustainable AI adoption.
• Act as a hands‑on contributor, working directly with program leadership, AI architects, data scientists, and engineering teams to support AI initiatives throughout their lifecycle.
• Establish monitoring, observability, and performance management capabilities for AI models, services, and AI‑powered applications.
• Define and manage processes for model deployment, versioning, validation, retraining, and lifecycle management.
• Ensure AI solutions meet operational requirements related to reliability, scalability, security, compliance, and business continuity.
• Develop and track key performance indicators (KPIs) and service metrics related to AI adoption, model performance, operational efficiency, and business value realization.
• Lead incident management, root‑cause analysis, and remediation efforts for AI‑related production issues.
• Collaborate with data engineering, platform, security, and infrastructure teams to optimize AI platform operations and service delivery.
• Drive the implementation of MLOps and LLMOps practices to support efficient deployment, monitoring, and governance of AI solutions.
• Establish governance processes to ensure compliance with Responsible AI principles, organizational policies, and regulatory requirements.
• Identify and mitigate operational, technical, security, and governance risks associated with AI deployments.
• Support the development and execution of change management and adoption strategies to maximize the value of AI investments.
• Translate operational insights and performance data into actionable recommendations for improving AI effectiveness and business outcomes.
• Demonstrate strong stakeholder management and communication skills, particularly when engaging with senior leadership and cross‑functional teams.
• Operate effectively within a fast‑paced, dynamic environment, delivering measurable outcomes and driving continuous operational excellence.
• Preferred Qualifications
• Extensive experience in AI/ML operations, platform engineering, MLOps, Dev Ops, or enterprise technology operations.
• Strong understanding of Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and AI platform ecosystems.
• Experience implementing and managing MLOps, LLMOps, model governance, and AI monitoring frameworks in enterprise environments.
• Proven expertise with cloud‑based AI and data platforms, automation tools, monitoring solutions, and CI/CD pipelines.
• Strong analytical and problem‑solving skills with the ability to translate operational data into strategic improvements.
• Demonstrated experience leading large‑scale AI transformation or operational excellence initiatives.
• Excellent communication, stakeholder engagement, and leadership capabilities.

This role is ideal for a specialist who can bridge AI strategy and day‑to‑day operations, ensuring that enterprise AI solutions remain reliable, governed, scalable, and aligned with business objectives.

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