Design and oversee the development of scalable generative AI systems and enterprise-grade AI platforms.
Establish robust architectures that support model training, inference, monitoring, and lifecycle management in production environments.
Direct the selection, customization, and enhancement of state-of-the-art generative AI and large language models.
Develop and execute APIs, microservices, and integration frameworks to incorporate AI capabilities into enterprise applications.
Ensure that AI platforms meet stringent standards for performance, reliability, security, and scalability, while also adhering to data governance and privacy regulations.
Collaborate closely with product, engineering, and business teams to outline technical requirements and approaches to AI architecture.
Architect end-to-end pipelines for deploying and monitoring AI models, ensuring seamless integration with existing systems.
Guide architectural decisions for LLM applications, AI workflows, and distributed AI infrastructure.
Institute best practices for ethical AI development, including strategies to mitigate risks like model hallucinations, bias, and reliability challenges.
Provide technical mentorship and guidance to engineering teams, while contributing to the formulation of long-term technology strategies and the advancement of AI platforms.

More than 4 years of experience in roles related to software engineering or architecture, with significant involvement in AI/ML systems.
Extensive knowledge of contemporary neural network architectures, such as Transformers, CNNs, and RNNs.
Demonstrated ability in developing scalable and distributed architectures for applications driven by AI.
Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
Proficient in containerization and orchestration technologies, especially with Docker and Kubernetes.
Strong understanding of microservices architecture, RESTful APIs, and the design of distributed systems.
Familiarity with MLOps / LLMOps pipelines, covering aspects like model training, deployment, monitoring, and lifecycle management.
Reasonable understanding of large-scale data systems and modern database technologies.
Adept at transforming business requirements into scalable AI solution architectures.
Excellent documentation skills for architectural designs, workflows, and technical decision-making processes.
Ability to thrive in a startup or fast-paced environment, demonstrating a strong sense of ownership and leadership.

AI Solutions Architect

Key skills