Senior Artificial Intelligence Architect

Join SADA as a Senior Artificial Intelligence Architect

Your Mission 

As a Senior Artificial Intelligence Architect at SADA, you will work in a fast-paced, highly-skilled team developing state-of-the-art enterprise solutions using a wide variety of artificial intelligence technologies. You will work directly with customers, engineers, sales teams and partners to deliver high quality professional service engagements to SADA’s customers. SADA is a premier partner of Google Cloud Platform (GCP), and as such, your implementations will focus on enabling customers to best utilize GCP or to demonstrate its capabilities. 

You will be responsible for building cloud-native artificial intelligence solutions using Google’s Vertex AI platform and all related technologies, such as Gemini large language models, Vertex AI, LangChain, Agent Development Kit, Vector Search and more. You may also be responsible for implementing domain-specific solutions such as Vertex AI Search for Retail or Contact Center AI Platform. This is a hands-on role that will include both architecting and implementing AI solutions.

Artificial intelligence is an extremely dynamic and quick-changing discipline. Therefore, your approach for learning new technology will be as important as any prior knowledge. We are looking for a “professional tinkerer” with a passion for continuous learning and a knack for problem solving. Someone that learns fast and pivots even faster. That always says “I’ll figure it out” instead of “I don’t know.”

Your day-to-day will consist of the following activities:

• Implementing AI–based solutions for SADA clients across all project stages, from discovery and architecture, to development, testing and launch
• Providing subject matter expertise and assistance to SADA clients and colleagues on artificial intelligence topics

• Collaboration with client stakeholders managing the project, including other engineers and Director-level client resources
• Creating technical documentation and leading solution design discussions
• Assisting with technical pre-sales discussions and the creation of statements of work 

Expectations

Customer-Facing - Daily interactions with customers, including standups or sales meetings; at other times, weekly/bi-weekly as for sprint planning, reviews/retrospectives, or demos. These interactions will be with roles ranging from engineers to key executive stakeholders.

Travel - Up to 35% travel to customer sites, conferences, and other related events.

Job Requirements

Required Credentials:

• One of the following (within 90 days of hire):
• Google Professional Machine Learning Certification
• Google Professional Data Engineer Certification

Required Qualifications:

• 4+ years of relevant work experience in technical consulting, software development or cloud engineering
• 1+ years of relevant work experience designing and implementing Generative AI solutions, including the use of large language models, model fine tuning, vector embeddings, and AI application frameworks to build retrieval augmented generation and multimodal workloads, preferably using Vertex AI on GCP
• Strong consultative skills, including the ability to translate complex AI concepts into actionable business strategies and solutions
• Ability to communicate complex technical concepts to a broad range of internal and external stakeholders
• Expertise in development using Python, and familiarity with other programming languages such as JavaScript, Go or Java
• Comfortable developing with frontend web frameworks such as Streamlit, Gradio or React
• Experience designing and implementing serverless and containerized solutions on common deployment runtimes, preferably Cloud Run, Google Kubernetes Engine, or Vertex AI on Google Cloud Platform
• Experience building and maintaining high-quality, developer-friendly server-side code, such as webhooks, cloud functions, and data pipelines
• Experience with full stack development, including setting up cloud infrastructure, database services and application lifecycle management
• Ability to architect, scope, and prioritize work based on feedback from the customer or internal teams.
• Experience working with analytical and transactional database systems, including SQL databases like MySQL, PostgreSQL or BigQuery
• Experience participating in sales calls
• Experience in business or technical consulting

Useful Qualifications:

• Exposure to containers and container orchestration, such as Docker

• Experience working with interactive development environments like JupyterLab and Vertex AI Workbench
• Exposure to model serving frameworks such as LLM and FastAPI and model training frameworks such as PyTorch and TensorFlow

• Experience in writing automated tests, including unit, integration, and acceptance tests
• Experience monitoring and scaling workloads based on latency or throughput demands