AI Architect

Sorenson Communications•Salt Lake City, UT

About The Position

Come be a part of our mission and make a meaningful and positive impact with the industry leading provider of language services for the Deaf and hard-of-hearing! Full time Benefits Paid Vacation Time and Paid Sick Time and Paid Holidays 401k 6% match with immediate vesting Nationwide Medical Insurance plans and coverage (Medical, Dental/Orthodontia, Vision) TeleDoc HSA company match 3 Medical plan options including a Low Deductible PPO Medical Plan Offering Employee Assistance Program Engaged Employee Resource Groups Outstanding Learning and Career Development Opportunities Pay Range: Actual pay may vary up or down depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for incentive compensation. Applicants must be legally eligible to work in the United States to be considered. Visa sponsorship is not available for this role Job Summary The AI Architect is responsible for designing and operationalizing the enterprise applied AI architecture that enables scalable, secure, and governed AI deployments. This role ensures AI solutions integrate effectively with Sorenson’s existing technology ecosystem—including enterprise data platforms, integration services, security frameworks, and cloud infrastructure—while maintaining alignment with enterprise architecture standards. Working closely with engineering, data, security, and program leadership, the AI Architect defines the architectural patterns, reusable components, and technical guardrails that allow AI initiatives to move efficiently from pilot to production while maintaining reliability, security, and governance compliance.

Requirements

Minimum 4 Year / Bachelors Degree In Computer Science, Software Engineering, Information Systems, or related field.
8 Years experience designing and implementing enterprise-scale AI or machine learning architectures.
Strong background prototyping in Python, distributed systems, APIs, microservices architecture, and cloud-native platforms.
Experience integrating AI or ML capabilities with enterprise systems and data platforms.
Deep familiarity with LLM architectures, RAG pipelines, and AI orchestration frameworks.
Experience implementing architecture patterns that support secure and scalable AI deployments.
Ability to collaborate across engineering, data, security, and business teams.
Strong understanding of enterprise architecture principles and modern cloud architectures.
Deep knowledge of AI application architectures including LLM integration, RAG pipelines, and AI service orchestration.
Familiarity with AI governance, security, and compliance considerations.
Experience designing reusable architecture frameworks and technical reference patterns.
Ability to evaluate emerging AI technologies and recommend enterprise-ready solutions.
Strong collaboration and communication skills with both technical and business stakeholders.
Ability to translate architectural vision into practical engineering guidance.
Strong analytical and problem-solving skills in complex enterprise environments.

Nice To Haves

Graduate Degree In Computer Science, Data Engineering, or related discipline.
Experience implementing AI platform or AI gateway architectures.
Experience working with enterprise data platforms such as Databricks, Snowflake, or similar environments.
Familiarity with vector databases, embedding pipelines, and retrieval frameworks.
Experience implementing DevSecOps practices within AI or ML environments.
Experience working within governance-heavy or compliance driven regulated enterprise environments.

Responsibilities

AI Architecture Design & Standards Establish enterprise Applied AI Architecture supporting AI-enabled products and internal capabilities.
Define architectural patterns for AI integration across Sorenson’s user interfaces, domain services (and microservices), integration layers, and enterprise data lake and data platforms.
Establish and maintain architecture standards and adaptors for LLM integration, RAG pipelines, prompt management, and AI orchestration frameworks.
Define reusable architectural components that accelerate development and ensure consistency across AI initiatives.
Ensure alignment between AI architecture and broader enterprise architecture strategy.
AI Gateway & Platform Architecture Design and oversee the implementation of the AI Gateway, enabling secure and governed contracts and access to AI models and services.
Establish provider abstraction and model routing strategies to support multiple model providers while avoiding vendor lock-in.
Define standards for model access APIs, request routing, and policy enforcement layers.
Implement architecture patterns for AI observability, performance monitoring, and cost management.
Ensure AI services integrate with enterprise identity, security, and API management frameworks.
RAG & Context Architecture Define enterprise standards for Retrieval-Augmented Generation (RAG) architectures.
Establish governance-aware approaches to data retrieval including source approval, indexing strategies, and retrieval policies.
Define patterns for vector stores, embedding pipelines, and context management frameworks.
Ensure RAG implementations align with enterprise data governance policies and data classification requirements.
Enable scalable knowledge access across enterprise systems while maintaining data security and compliance.
Applied AI Solution deployment Rapid prototyping of AI solution patterns including LLM agents, RAG pipelines, and workflow automations.
Partner with business stakeholders to translate operational problems into AI solutions
Validate model performance, prompt strategies, and retrieval approaches before production deployment
AI SDLC & Engineering Integration Embed architectural guardrails into the AI software development lifecycle (AI SDLC).
Define architecture requirements for model evaluation, prompt versioning, and deployment pipelines.
Partner with DevSecOps teams to ensure AI systems follow established CI/CD practices.
Establish architecture patterns for production monitoring, drift detection, and rollback strategies.
Ensure AI systems meet reliability, scalability, and operational readiness requirements.
Security & Responsible AI Architecture Collaborate with Cyber Security and DevSecOps teams to embed security controls and risk management practices into AI architectures.
Define safeguards for prompt injection, data exposure, and tool misuse within AI systems.
Ensure AI systems adhere to enterprise policies around data protection, identity access controls, and regulatory compliance.
Support implementation of governance-as-code frameworks within AI platforms.
Contribute to threat modeling and risk assessments for AI-enabled solutions.
Cross-Functional Architecture Leadership Partner with Data Engineering, Data Governance, Security, and Platform Engineering teams to ensure architectural alignment.
Provide technical guidance and architecture reviews for AI initiatives across business units.
Support the AI Program Manager in evaluating the technical feasibility and architecture readiness of new AI initiatives.
Contribute to the development of reusable architecture assets, templates, and reference implementations.
Act as a technical advisor to AICOE leadership on emerging AI technologies and architectural best practices.
Other duties as assigned.

Benefits

Full time
Benefits
Paid Vacation Time
Paid Sick Time
Paid Holidays
401k 6% match with immediate vesting
Nationwide Medical Insurance plans and coverage (Medical, Dental/Orthodontia, Vision)
TeleDoc
HSA company match
3 Medical plan options including a Low Deductible PPO Medical Plan Offering
Employee Assistance Program
Engaged Employee Resource Groups
Outstanding Learning and Career Development Opportunities