Principal Architect
3 weeks ago
Position Overview:
We are seeking a Principal Architect with extensive expertise in software systems and AWS services, specifically in machine learning (ML) infrastructure. In this role, you will define and deliver architecture for advanced ML workflows and data-driven systems by leveraging AWS services such as Lex, S3, Amazon SQS, EC2, RDS, and agent-based software systems. This position requires a blend of leadership, strategic vision, and hands-on technical skills to build robust, scalable, and efficient solutions.
Key Responsibilities:
1. Architectural Leadership
o Design, implement, and optimize large-scale AWS ML infrastructure and software systems.
o Ensure performance, scalability, security, and resilience of the overall architecture.
2. Machine Learning Infrastructure
o Build systems using AWS services, including Lex for conversational interfaces, S3 for storage, SQS
for queuing, and other AWS tools.
3. Cross-Functional Collaboration
o Partner with Data Scientists, ML Engineers, Software Developers, DevOps, and Product Managers
to deliver technical solutions that align with business objectives.
4. Cloud Architecture Best Practices
o Define and implement cloud infrastructure best practices focused on performance optimization,
fault tolerance, cost management, and scalability for ML pipelines and agent-based systems.
5. Solution Design
o Develop high-level architecture that integrates various AWS services, databases, and agent-based
and traditional software systems.
6. Mentorship
o Mentor technical team members, fostering knowledge sharing and professional growth.
7. Strategic Input
o Contribute to the long-term technical vision and define roadmaps for technology and ML initiatives.
8. Continuous Improvement
o Stay updated with emerging technologies and AWS advancements in ML and cloud architecture to maintain a competitive edge.
Required Qualifications:
1. Experience:
o 7+ years of experience in designing, architecting, and deploying ML infrastructure on AWS.
o Hands-on expertise with AWS services such as Lex, S3, SQS, and other AWS-based data processing
tools.
2. AWS Proficiency:
o In-depth knowledge of AWS services, particularly for ML workflows, data lakes, and real-time
systems.
3. Architectural Expertise:
o Proven track record of creating scalable and reliable architectures for ML and agent-based software
systems.
4. ML Systems Understanding:
o Experience with ML frameworks and integration with AWS ML services such as SageMaker.
5. Cloud Architecture:
o Expertise in cloud design patterns, including microservices, serverless computing, containerization (ECS, EKS), and event-driven architectures.
6. Databases and Data Pipelines:
o Proficiency in AWS database systems (RDS, DynamoDB) and building efficient ETL processes and
data lake architectures.
7. Leadership and Mentorship:
o Demonstrated ability to lead teams and provide technical direction for complex projects.
8. Communication:
o Excellent written and verbal communication skills to articulate complex technical concepts to
stakeholders across all levels.
Preferred Skills (Optional):
• AWS Certifications (e.g., AWS Certified Solutions Architect – Professional).
• Familiarity with agent-based software systems and their applications in data-driven environments.
• Hands-on experience with DevOps practices, including CI/CD pipelines and infrastructure-as-code tools like CloudFormation or Terraform.
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