AI Platform Solution Architect

1 day ago

Bucharest, Bucureşti, Romania Decillion Digital Limited Full time 60,000 - 180,000 per year

Role: AI Platform Solution Architect

Location: Bulgaria

Overview:

The AI Platform Solution Architect serves as a key technical leader responsible for designing, developing, and implementing scalable, high-performance artificial intelligence (AI) platforms and solutions that meet diverse business needs. This role focuses on architecting end-to-end AI ecosystems that enable organizations to operationalize AI/ML workloads, accelerate innovation, and achieve measurable business impact.

The Solution Architect works collaboratively with cross-functional teams—including data scientists, engineers, IT operations, and business stakeholders—to ensure that AI platforms are secure, reliable, and optimized for performance. The position requires leveraging advanced technologies across AI/ML frameworks, high-performance computing (HPC), cloud-native platforms, and data engineering to build robust, future-ready AI solutions.

Key Responsibilities:

  • Design and implement scalable, secure, and high-performance AI/ML platform architectures for enterprise and hybrid environments.
  • Collaborate with data science, engineering, and business teams to define end-to-end AI/ML workflows, from data ingestion to model deployment.
  • Establish MLOps frameworks to automate model training, testing, deployment, and monitoring.
  • Integrate advanced cloud and on-premise infrastructure solutions to support complex AI workloads.
  • Optimize data pipelines and compute resources to enhance model performance and cost efficiency.
  • Define best practices for AI governance, compliance, and lifecycle management.
  • Evaluate emerging AI and data technologies to ensure the platform remains cutting-edge and adaptable.
  • Provide technical leadership and mentorship across engineering and solution delivery teams.

Technical Skills & Experience:

  • Deep understanding of AI/ML frameworks such as TensorFlow, PyTorch, and Keras.
  • Expertise in MLOps practices and automation of end-to-end machine learning workflows.
  • Strong experience with cloud and hybrid platforms, including AWS, Azure, and Google Cloud.
  • Proficiency in containerization and orchestration technologies such as Docker and Kubernetes.
  • Experience with infrastructure-as-code tools (e.g., Terraform, Ansible) for scalable environment provisioning.
  • Knowledge of data engineering and pipeline orchestration tools for managing large-scale data workflows.
  • Familiarity with high-performance computing (HPC) environments and GPU-based AI workloads.

Preferred Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Proven track record in architecting and deploying enterprise-grade AI/ML platforms.
  • Strong communication and stakeholder management skills.
  • Ability to stay current with emerging trends in AI, data, and cloud ecosystems.

Job Types: Full-time, Contract

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