D
Devoteam
AI Engineer

Distributed Cloud | AI Data Architect

On-siteSeniorAI Engineerposted 8mo ago
Role summaryAI-generated

This role demands a strategic leader to architect scalable AI/ML systems with end-to-end MLOps, bridging data engineering and cloud-native infrastructure for enterprise-grade deployments. The candidate will shape governance frameworks and high-performance pipelines while ensuring seamless integration with business systems.

Skills required

About this role

We are seeking a seasoned and strategic Data & AI Architect to lead the vision, design, and governance of our entire data science and machine learning ecosystem. This pivotal role combines data architecture expertise with MLOps principles to ensure our AI solutions are reliable, scalable, and integrated into core business systems.

Key Responsibilities:

  • Define and Govern AI/ML Architecture: Establish the end-to-end MLOps strategy and architecture for the entire ML lifecycle, covering experimentation, training, versioning, deployment, and monitoring of models.
  • Infrastructure Design: Design and implement scalable infrastructure (cloud-native, utilizing Kubernetes/GKE/EKS/AKS) for model training, serving, and high-performance inference.
  • Data Platform Integration: Collaborate with Data Engineering teams to design efficient Feature Stores, data labeling processes, and high-speed data integration between the Data Warehouse/Lake and ML pipelines.
  • MLOps Implementation: Drive the adoption of robust CI/CD and automation frameworks for code and model deployment, ensuring model lineage, security, and reproducibility.
  • Architecture Strategy: Evaluate and recommend new tools, platforms, and technologies to optimize the overall Data & AI platform for performance, cost-efficiency, and future growth.
  • Leadership & Governance: Provide technical leadership and establish governance frameworks for data quality, model auditing, and responsible AI deployment.

Qualifications

  • 7+ years of progressive experience in Data Engineering, Software Architecture, or ML Engineering, with a clear focus on designing and scaling production-grade ML/AI systems.
  • Mandatory hands-on expertise with MLOps principles and tools, including containerization (Docker) and orchestration (Kubernetes/K8s).
  • Deep knowledge of at least one major Cloud platform (AWS, Azure, or GCP) and its respective ML and data services (e.g., Vertex AI, SageMaker, Azure ML, BigQuery/Synapse).
  • Strong understanding of Data Architecture principles (Data Warehouse/Lake design, Data Modeling) and data governance.

Highly Valued Skills:

  • Experience with Feature Stores (e.g., Feast) or specialized data components for ML.
  • Practical experience designing GenAI (RAG) or streaming data architectures.
  • Relevant professional certifications in Cloud Architecture or MLOps.
  • Proficiency in Python and solid understanding of modern software architecture (e.g., microservices, APIs).
  • Excellent communication skills with the ability to define technical roadmaps and lead architectural discussions with senior stakeholders.

Additional Information

The Devoteam Group works for equal opportunities, promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity, dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.

Apply on DevoteamOpens in new tab
score your resume against this role

Similar open roles

M
NEW

Staff AI Engineer, SMAI

Micron·Hyderabad - Phoenix Aquila, India
On-siteStaffAI Engineer
yesterday
A
NEW

Principal AI Engineer

AVEVA·Bangalore, India; Hyderabad, India
On-siteSeniorAI Engineer
yesterday
SK
Sponsored

Land 5x More Interviews - Resume & Strategy

Shaqeeq Khan·Built this board, coached engineers from Netflix, Google, IBM, Amazon. 100+ grads placed.
CV ReviewLive One on One CallsStrategy
Book A Call
Apply on Devoteam
Distributed Cloud | AI Data Architect at Devoteam — Lisboa