Analytics and AI Solution Architect

Key Responsibilities

• Develop and implement cloud-native analytic applications and solutions using industry-leading cloud platforms such as Amazon Web Services, Google Cloud, and Azure.
• Design and coordinate cloud architecture across areas including application development, identity and access management, network and data management, and security.
• Define DevSecOps solutions and integrate them with cloud platforms, utilizing DevOps processes, automation, and target platforms.
• Build and design web services for cloud environments, orchestrating and automating cloud-based platforms.
• Develop responsive user interfaces utilizing HTML, JavaScript libraries, ensuring seamless performance across various form factors.
• Leverage data engineering expertise to build pipelines for structured and unstructured data and design databases using tools such as Databricks, Snowflake, NoSQL, and Vector databases in a Retrieval Augmented Generative AI architecture.
• Apply Lambda architecture, database design, and data modeling to support scalable and efficient cloud-based applications.
• Utilize agile methodologies to ensure disciplined execution, problem-solving, and adherence to Intel's core values.
• Collaborate with multidisciplinary teams to deliver AI/ML infrastructure solutions and big data cloud integrations, such as Spark and Splunk.
• Ensure robust information security practices in all facets of the development lifecycle.

Qualifications

• Minimum Qualifications: Bachelor's degree in Computer Science, Information Technology, or a related field. 9+ years of relevant experience with a bachelor's degree or 6+ years with a master's degree, or 4+ years with a PhD.
• Proficiency in cloud platforms including AWS, Google Cloud, and Azure, as well as web service design and orchestration.
• At least 5 years of expertise in database engineering, data modeling, and cloud-based big data tools such as Databricks, Snowflake, NoSQL and Vector databases.
• At least 5 years of experience with Lambda architecture design and DevSecOps integration.
• Technical proficiency in developing user interfaces using HTML, JavaScript libraries, and AWS frameworks.
• Knowledge of agile methodology and disciplined execution processes.

Preferred Qualifications

• Demonstrated experience in AI/ML infrastructure solutions, agentic AI, and MCP.
• Strong communication skills and the ability to collaborate effectively with cross-functional teams.
• Prominent ability to solve complex technical challenges and deliver innovative cloud-based solutions.