Solution Architect
Role details
Job location
Tech stack
Requirements
- AI & ML Frameworks: Familiarity with major AI/ML frameworks and services, including OpenAI GPT models, Google PaLM/Vertex AI, and Hugging Face Transformers library.
*SaaS AI & Data Platforms: Experience with leading SaaS AI & Data platforms in terms of agentic AI development, implementation, orchestration, AI guardrails
*Agentic AI Tooling: Exposure to frameworks and libraries for building AI agents and chains, such as LangChain ,Microsoft's Semantic Kernel.
*Retrieval Systems: Strong knowledge of search and retrieval technologies, including vector databases and semantic search.
*Cloud Services: Expertise in cloud ecosystems (AWS, Azure, Google Cloud Platform), including cloud AI services, serverless computing, containerization, and related DevOps tools.
*Programming & Scripting: Proficiency in programming languages commonly used for AI and integration, primarily Python and at least one general-purpose language.
*Data Platforms: Knowledge of modern data platforms, including relational databases, NoSQL stores, and data processing frameworks.
*Integration & APIs: Experience designing and using APIs and middleware, knowledge of event-driven architectures and message brokers.
*DevOps & MLOps: Familiar with CI/CD pipelines and infrastructure as code, understanding of MLOps principles and tools.
*Security & Compliance Tools: Comfort with technologies for securing AI applications, including identity and access management, encryption, and compliance tools.
*Collaboration & Design: Proficient with tools used in architecture and design documentation, including UML design tools and agile project management tools.
*Emerging Tech: Awareness of emerging tech such as knowledge graphs and reinforcement learning frameworks.