AWS Architect

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 : - 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 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 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 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 : - 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 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. (ref:hirist.tech)