AWS Architect - Python

Description :

We are seeking an experienced AI Solutions Engineering Manager or AWS Architect with Python experience 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.

This position is within our AI Centre of Excellence team, where we build cutting-edge automation solutions using Langraph, AWS Agentcore, Google Agentspace, Crew.ai, 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.

Responsibilities :

- 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.

- 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.

- 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.

- 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.

- Establish design standards and process documentation (PDD) to ensure consistent, organised 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.

- 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.

- Actively contribute to development work, focusing on high-impact improvements to maximise 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.

Requirements :

- 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.)

- 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 the ability to balance technical debt and feature delivery.

- Demonstrated ability to free teams from routine tasks to focus on higher-value, creative work.

- 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.

- Bachelor's 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, Crew.ai.

- 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.