AGCO is looking to hire candidates for the position of Systems Architect, AI Systems
We are seeking an experienced and innovative Systems Architect, AI Systems to lead the design, creation, and evolution of system architectures for AI solutions within our organization
The Systems Architect, AI Systems, is a critical role responsible for designing, implementing, and evolving scalable AI architectures that support and drive the company's AI and data strategies
The ideal candidate will have extensive experience in architecting, deploying, and managing AI solutions in cloud-based environments, with a focus on high performance, security, and interoperability
This role will work closely with data science, engineering, and delivery teams to ensure AI systems are seamlessly integrated across the organizations operations
Your Impact
AI Systems Architecture: Design and implement scalable architectures that support AI/ML models and data systems, optimizing for performance, cost-efficiency, and security
Cloud Platform Expertise: Leverage cloud environments (AWS, GCP, Azure) to architect solutions that support high-volume data processing, storage, and AI model deployment
Data Integration & Pipeline Design: Develop and oversee data pipelines that ensure smooth data flow between various sources and AI systems, incorporating best practices for ETL, data lakes, and real-time streaming
Model Deployment and Monitoring: Collaborate with ML engineers to establish CI/CD pipelines for model deployment, monitoring, and lifecycle management to ensure models remain reliable and efficient in production
Tool Evaluation and Adoption: Evaluate and recommend AI tools, libraries, and platforms that align with business goals, ensuring that the chosen technology stack can support complex AI and data requirements
Security and Compliance: Ensure all AI architectures meet security, regulatory, and compliance standards relevant to data handling, model deployment, and user access, particularly with regards to GDPR, CPRA, and industry-specific regulations
Documentation and Best Practices: Establish and maintain comprehensive documentation of architecture designs, policies, and processes, promoting best practices across the AI & Data Operations organization
Functional Knowledge
Advanced AI and Data Systems: Deep understanding of AI architectures, including distributed computing frameworks (e g, Apache Spark, Hadoop), data lakes, data warehousing, and MLOps
Cloud Infrastructure and Services: Proficient in AWS (SageMaker, Redshift, Lambda), Google Cloud Platform (BigQuery, Vertex AI), and/or Azure AI services, with a strong grasp of cloud-based data management and ML lifecycle management
Containerization and Orchestration: Skilled in Docker, Kubernetes, and other container management tools to ensure scalability and efficiency in model deployment and orchestration
Data Security and Governance: Familiar with data governance frameworks and security protocols, including encryption, authentication, and compliance requirements (GDPR, CPRA, etc ), especially as they relate to cloud-based AI solutions
Business Expertise
Experience in industries such as manufacturing, agriculture, or supply chain, particularly in AI and data use cases
Familiarity with regulatory requirements related to data governance and security
Experience with emerging technologies like edge computing, IoT, and AI/ML automation tools
Your Experience And Qualifications
Bachelors degree in computer science, data science, or related field
Masters degree or relevant certifications is preferred
Experience: 8+ years of experience in systems architecture, with at least 5 years focused on AI and data systems in a cloud environment
Programming Languages: Proficient in Python, Java, and SQL; familiarity with R, Scala, or other languages is a plus
MLOps Tools: Hands-on experience with MLOps tools and frameworks (e g, MLflow, Kubeflow, Airflow) for model tracking, versioning, and deployment
Data Engineering: Strong experience with ETL processes, real-time data streaming (Kafka, Spark Streaming), and data pipeline design
Analytical Skills: Strong problem-solving abilities with the capacity to analyze system requirements and design scalable solutions that meet both technical and business needs
Communication and Leadership: Excellent communication skills to explain complex architecture concepts to non-technical stakeholders, as well as the ability to lead technical discussions and mentor junior team members
Certifications: Relevant certifications are a plus (e g, AWS Certified Solutions Architect, Google Professional Data Engineer, Certified Kubernetes Administrator)
Your Benefits

Systems Architect, Artificial Intelligence

Job Description

Required Skills