AI Automation Engineer (Manager)

Job Purpose:

The AI Automation Engineer is responsible for designing, building, and delivering AI-driven automation solutions across the Bank using modern AI platforms, multi-model architectures, and cloud-based AI services, ensuring scalability, integration, and measurable business outcomes.

Key Responsibilities:

1. Report and provide regular updates to Head of AI, Data analytics, Automation and Process Excellence

2. Accountable for designing and delivering AI-driven automation solutions across multiple business units

3. Develop AI-enabled workflows using:

• Microsoft Copilot / Copilot Studio
• Microsoft Power Platform (workflow orchestration)
• Other platforms such as n8n, Dify and similar AI orchestration tools (advantage)

4. Design and implement agent-based automation solutions leveraging multiple AI models (LLMs)

5. Integrate AI automation with enterprise systems, including data platforms, APIs, and business applications

6. Design intelligent automation incorporating:

• AI decision-making
• workflow orchestration
• event-driven triggers

7. Develop automation solutions utilizing cloud-based AI services from:

• Microsoft Azure AI
• AWS AI/ML services
• Other public cloud AI platforms

8. Build and manage automation pipelines that support multi-model AI (LLM orchestration)

9. Ensure solutions are designed with:

• scalability
• resilience
• auditability

10. Design exception handling and fallback logic for AI-based workflows

11. Ensure all implementations comply with:

• Data governance policies
• Technology standards
• Regulatory and security requirements

12. Conduct SIT, UAT, and support deployment and production monitoring

13. Optimize automation performance, including:

• AI accuracy
• processing time
• cost efficiency (compute/API usage)

14. Maintain complete technical documentation and solution governance artifacts

15. Collaborate with internal stakeholders, vendors, and cloud/technology providers

16. Manage technical escalations and continuously improve solution quality

Requirements:

1. Education

• Bachelor's Degree in Computer Science, IT, Engineering or related field
• Cloud or AI certifications are an advantage

2. Experience

Minimum 5 – 8 years experience in:

• Automation development
• AI solution engineering
• Cloud-based application development
• Experience in banking / financial services is preferred

3. Technical Skills (Mandatory)

• AI workflow and automation design
• Experience with Copilot / AI agent frameworks
• Cloud platforms (Azure / AWS)
• API integration and microservices architecture
• Data integration (structured & unstructured)

4. Technical Skills (Strong Advantage)

Experience in multi-model AI (LLM orchestration)

Hands-on with:

• n8n (workflow automation orchestration)
• Dify (LLM app / agent builder platform)

Experience with:

• Azure OpenAI / AWS Bedrock / similar services

Knowledge of:

• Prompt engineering
• AI agent design
• OCR / NLP / document intelligence

5. Functional Competencies

• Strong analytical and solution design skills
• System thinking and architecture mindset
• Attention to detail and quality control
• Ability to handle complex, cross-system workflows