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Open nowPosted today

Lead Consultant - AI Ops & Error Handling

MyCareersFuture95,505 open roles

Pay
SGD 5,500 – SGD 8,500 a month
Where
Central, Singapore
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Your applicationOpen nowLead Consultant - AI Ops & Error HandlingMyCareersFuture · Central, Singapore
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The clock on this job

Early applications get read.

10.1% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 8 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.0%3 days
  3. 10.1%7 days
  4. 15.8%14 days
  5. 34.0%30 days
This job: posted today

MyCareersFuture median: 8 days open

The posting

Role Overview

Lead the design, implementation, and delivery of one of three critical workstreams: Generic Error Handling, Auto-Recovery & Dependency (AI Ops) You will serve as the technical authority for your workstream, driving solution architecture, client engagement, and team leadership to deliver measurable business outcomes within an aggressive timeline.

Key Responsibilities

Technical Leadership

  • Lead end-to-end design and implementation of your assigned workstream solution
  • Translate business requirements into scalable, maintainable technical architectures
  • Design and implement integrations with BANK systems (API, Grafana, Cloud, monitoring tools)
  • Conduct technical reviews and ensure solution quality meets enterprise standards
  • Troubleshoot complex issues across application layers, integrations, and cloud services

Client Engagement & Consulting

  • Engage BANK stakeholders to gather requirements, propose solutions, and drive technical discussions
  • Serve as trusted technical advisor, providing strategic recommendations to senior leadership
  • Present solution designs, progress updates, and business value demonstrations
  • Manage stakeholder expectations and ensure alignment across teams

Delivery Management

  • Own delivery of your workstream within scope, schedule, and budget
  • Drive SIT/UAT activities, ensure solution quality, and support go-live and hypercare phases
  • Identify and mitigate technical and delivery risks proactively
  • Coordinate with other Lead Consultants to ensure cross-workstream integration

Team Development

  • Mentor Senior Consultants, Consultants, and Associate Consultants on best practices
  • Provide technical guidance on implementation approaches and problem-solving
  • Foster a culture of continuous learning and professional growth
  • Contribute to reusable assets, frameworks, and internal capability building

Requirements

Essential

  • Bachelor's degree in Computer Science, Engineering, Information Technology or related field
  • 9-12 years of relevant experience in software development, system integration, or technical consulting
  • Proven track record leading complex technical projects from design through production
  • Strong expertise in at least one workstream area:
  • Error Handling: API design, error frameworks, observability tools (Grafana, Splunk)
  • Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes, PCF)
  • Strong analytical, problem-solving, and structured thinking capabilities
  • Excellent communication, presentation, and stakeholder management skills
  • Ability to work independently, take ownership, and deliver under tight timelines

Preferred

  • Experience with financial services or banking systems
  • Familiarity with BANK technology stack (API, MFE, backend systems)
  • Knowledge of AI/ML tools and platforms (e.g., AWS SageMaker, Azure ML)
  • Experience with observability tools (Grafana, Prometheus, ELK stack)
  • Understanding of DevOps practices and CI/CD automation
  • Certification in relevant technologies (AWS, Azure, Kubernetes, ITIL)

What You'll Deliver

  • Fully functional solution for your workstream, deployed to production
  • Technical architecture documentation and design specifications
  • Integration with existing BANK systems and monitoring tools
  • Knowledge transfer and training materials for BANK teams
  • Measurable business outcomes (e.g., reduced incident escalations, improved error visibility)
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