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 :

• 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)