AI Solutions Engineering Manager

Position Overview

We are seeking an experienced AI Solutions Engineering Manager to lead and transform our AI Centre of Excellence with enterprise grade engineering capabilities. This role requires a hands-on technical leader who will establish software engineering best practices, implement robust DevOps processes, and scale our AI / Automation solutions with enterprise-grade reliability and maintainability.

About the Role

This position is within our AI Centre of Excellence team, where we build cutting-edge automation solutions using Langraph, AWS Agentcore, Google Agentspace, , UiPath, Custom Python solutions and other advanced AI/Automation platforms. As the Engineering Manager, you will bridge the gap between our innovative AI development capabilities and enterprise-grade software delivery practices.

Key Responsibilities

Leadership & Team Development

• Manage and mentor a team of AI/Automation solution developers, providing technical guidance on best practices in solution development and deployment
• Foster a collaborative environment focused on code reviews, pair programming, and knowledge sharing
• Establish clear expectations and performance metrics for solution quality and delivery

Software Engineering Excellence

• Implement version control best practices with clear commit messages, feature branches, and stable main branch management
• Establish CI/CD pipelines for automated builds, tests, and deployments to enable faster, safer releases
• Drive adoption of clean code principles (KISS, YAGNI, DRY, SOLID) to reduce complexity and improve maintainability
• Implement comprehensive logging and monitoring strategies for audit trails and production support

DevOps & Infrastructure Management

• Design and implement multi-environment deployment strategies (Development UAT QA Production)
• Establish Infrastructure as Code (IaC) practices using tools like Terraform or CloudFormation
• Create robust testing environments to prevent production issues and enable safe experimentation
• Implement automated testing frameworks for AI/Automation solutions including unit, integration, and end-to-end testing

Cloud & Platform Engineering

• Lead cloud deployment initiatives on AWS and GCP platforms
• Design scalable, secure, and cost-effective cloud architectures for AI solutions
• Implement cloud-native, serverless deployment strategies for flexible scaling and global accessibility
• Establish monitoring, alerting, and observability practices for production AI systems

Solution Architecture & Best Practices

• Establish design standards and process documentation (PDD) to ensure consistent, organized automation development
• Implement configuration management practices to eliminate hard-coding and enable business user flexibility
• Create reusable component libraries and shared workflows to accelerate development and improve maintainability
• Establish quality assurance processes including testing protocols and output validation procedures

Cross-Functional Collaboration

• Interface with various internal teams to coordinate deployment, environment setup, and integration requirements
• Translate business requirements into technical specifications and implementation plans
• Collaborate with security, compliance, and governance teams to ensure solutions meet enterprise standards
• Provide technical expertise to support business stakeholders and solution adoption

Hands-On Technical Contribution

• Actively contribute to development work, focusing on high-impact improvements to maximize team productivity
• Troubleshoot complex technical issues and provide architectural guidance
• Prototype new technologies and evaluate their fit for our solution stack
• Participate in code reviews and provide technical mentorship

Required Qualifications

Technical Experience

• 8+ years of software development experience with strong programming skills in Python, Java, or similar languages
• 3+ years of engineering management experience leading technical teams
• 5+ years of cloud platform experience (AWS/GCP) including containerization, orchestration, and serverless technologies
• 3+ years of DevOps experience including CI/CD, Infrastructure as Code, and automated testing
• Experience with AI/ML frameworks and tools (TensorFlow, PyTorch, Hugging Face, etc.)

Leadership & Process Skills

• Proven track record of implementing software engineering best practices in development teams
• Experience establishing and managing multi-environment deployment processes
• Strong project management skills with ability to balance technical debt and feature delivery
• Demonstrated ability to free teams from routine tasks to focus on higher-value, creative work

Domain Knowledge

• Understanding of AI/ML model deployment, monitoring, and lifecycle management
• Knowledge of automation governance, security, and compliance requirements
• Experience with enterprise software delivery and production support processes
• Familiarity with security, governance, and compliance best practices for AI implementations

Preferred Qualifications

• Bachelors degree in computer science, Engineering, or related field
• AWS/GCP certifications (Solutions Architect, DevOps Engineer)
• Experience with specific tools in our stack: UiPath, Langraph, AWS Agentcore, Google Agentspace,
• Experience with monitoring and observability tools (DataDog, Grafana, etc.)
• Knowledge of enterprise identity and access management systems
• Previous experience in a similar role within our company or industry

Key Success Metrics

• Reduction in production incidents and faster resolution times
• Improved deployment frequency and lead time to production
• Enhanced code quality metrics and reduced technical debt
• Team productivity improvements and developer satisfaction