Description : 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 teamsincluding data scientists, engineers, IT operations, and business stakeholdersto 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-premises 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 :
Bachelors or Masters 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 ecosystemsLocation : Bulgaria
(ref : hirist.tech)