Machine Learning Engineer Enterprise AI Solutions Architecture

We are seeking a Machine Learning Engineer to help design and evolve enterprise AI systems and architectures that enable scalable, secure, and high-impact AI adoption across the organization.

This role focuses on defining end-to-end AI solution patterns involving LLMs, APIs, Retrieval-Augmented Generation (RAG), vector search, intelligent agents, orchestration workflows, Snowflake, cloud platforms (AWS and Azure), and enterprise data integration. The position partners closely with engineering, data, operations, business applications, security, and governance teams to develop reusable frameworks that accelerate AI delivery while supporting security, compliance, and operational requirements.

This position may require occasional travel for collaboration and planning activities.

• Design enterprise AI solution architectures that align business needs with scalable implementation approaches.
• Collaborate with cross-functional teams to translate business challenges into practical technical solutions.
• Identify and address gaps related to scalability, data readiness, interoperability, and operational adoption.
• Develop reusable frameworks, standards, and patterns that improve consistency across AI initiatives.
• Evaluate solution options and communicate trade-offs involving performance, cost, risk, and business value.
• Guide architecture decisions that support responsible AI adoption and long-term maintainability.
• Promote best practices, governance standards, and scalable implementation approaches across teams.
• Stay current on emerging AI technologies and assess their applicability to business objectives.

• 5–8 years of relevant experience in engineering, architecture, data, or enterprise technology roles.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
• Experience designing or supporting enterprise AI solutions involving Generative AI, LLMs, RAG, intelligent agents, or related technologies.
• Strong understanding of enterprise architecture principles, system design, integration patterns, and scalable delivery models.
• Experience working with cloud platforms such as AWS and/or Azure.
• Experience collaborating with both technical and business stakeholders to solve complex organizational challenges.
• Ability to evaluate ambiguous problems, structure recommendations, and clearly communicate trade-offs.
• Strong judgment balancing innovation, security, governance, operational feasibility, and business value.
• Excellent collaboration and communication skills with the ability to influence across teams.
• Familiarity with risk management, governance, compliance, and enterprise control environments.

• Hybrid opportunity located in Austin, TX
• Applicants must be authorized to work in the U.S. without sponsorship
• Competitive compensation, benefits, flexible time off, and career development opportunities