AI Solutions Delivery

NTT SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

A global technology provider is seeking an operational leader to head the AI Solution Delivery team in Singapore. This role requires overseeing a team of 15–20 AI engineers responsible for delivering and supporting AI-driven solutions. Candidates should have over 12 years of IT services experience and a solid understanding of AI/ML technologies. Responsibilities include implementing AI solutions, managing team operations, and driving skilled capability development within the team. Competitive compensation and professional development opportunities are offered.

Qualifications

• 12+ years in IT services/consulting, with 3-5 years in AI/ML solution delivery leadership.
• Proven experience managing delivery teams of 10-20+ engineers.
• Hands-on understanding of AI/ML tech stack.

Responsibilities

• Oversee end-to-end implementation of AI solutions.
• Manage day-to-day project execution, ensuring quality metrics are met.
• Establish and run AI operations frameworks.

Skills

Leadership

AI/ML technology understanding

Problem-solving

Communication

Team management

Tools

AWS

Azure

GCP

LangChain

CI/CD pipelines

Job description

We are seeking a hands‑on operational leader to head our AI Solution Delivery team. This role will oversee a team of 15–20 AI engineers focused on building, deploying, and supporting Generative AI (GenAI), Agentic AI, and broader AI‑driven solutions. The leader will be accountable for day‑to‑day operations, capability development, and ensuring reliable delivery for client projects. Unlike sales or business development roles, this position is dedicated to delivery excellence, team leadership, and operational governance

Team & Capability Development

• Lead, mentor, and grow a team of 15–20 AI engineers and specialists across multiple AI disciplines.
• Define and implement capability development plans (skills roadmap, certifications, training) to keep the team aligned with emerging AI technologies.
• Foster a culture of engineering excellence, collaboration, and continuous improvement.

AI Solution Delivery

• Oversee end‑to‑end implementation of AI solutions (design, build, test, deploy, and support).
• Ensure solutions are scalable, reliable, and compliant with enterprise standards.
• Manage day‑to‑day project execution, ensuring delivery timelines, SLAs, and quality metrics are consistently met.
• Provide hands‑on technical guidance where needed (architecture reviews, debugging issues, solution optimization).

AI Operations (AIOps, LLMOps, AgentOps)

• Establish and run AI operations frameworks for monitoring, retraining, fine‑tuning, and maintaining AI systems in production.
• Implement operational dashboards and reporting mechanisms to track model performance, uptime, and drift.Ensure adherence to AI governance, data privacy, and ethical AI standards.
• Drive incident management and continuous improvements for production AI systems.

Operational Leadership

• Manage resource allocation, workload distribution, and day‑to‑day operations of the AI delivery team.
• Standardize delivery processes and playbooks to ensure repeatability and consistency.
• Collaborate with solution architects, cloud teams, and data engineering teams to ensure smooth integration of AI solutions.
• Act as the escalation point for technical and operational issues within delivery.

Qualifications & Experience

• 12+ years in IT services/consulting with at least 3–5 years in AI/ML solution delivery leadership.
• Proven experience managing delivery teams of 10–20+ engineers.
• Hands‑on understanding of AI/ML tech stack, including:
  • GenAI & LLMs (LangChain, RAG, orchestration frameworks, vector databases).
  • MLOps/LLMOps/AgentOps practices (CI/CD pipelines, model monitoring, retraining).
  • Cloud AI services (AWS, Azure, GCP).
• Strong track record of running day‑to‑day operations, governance, and delivery management.
• Excellent problem‑solving, communication, and team management skills.

Preferred Skills

• Experience in productionizing AI solutions at scale.
• Exposure to agentic AI use cases (AI agents for automation, workflows, etc.).
• Certifications in cloud AI/ML platforms.
• Practical experience with AI governance frameworks.