AI Solutions Architect

Solution Architecture & Innovation

Translate business challenges into well-scoped AI solutions, balancing feasibility, value, cost, and speed.
Architect end-to-end AI systems, including data ingestion, model training, inference pipelines, monitoring, and governance.
Design and refine LLM/RAG architectures, agent workflows, and prompt engineering patterns.
Rapidly explore emerging tools/techniques to extend AI capabilities across the organization.
Build reusable reference architectures and best practices for internal teams.

Technical Leadership & Execution

Partner with engineering, data science, and product teams to guide implementation.
Conduct PoCs, prototypes, and pilots to validate technical suitability before scaling.
Ensure solutions meet performance, security, compliance, and cost-efficiency requirements.
Integrate AI capabilities into existing systems, both cloud and legacy.
Work with MLOps/DevOps to establish robust CI/CD, observability, and lifecycle management.

Strategy, Governance & Cross-Functional Collaboration

Complement the Product team by defining the technical AI/ML roadmap, assessing feasibility, shaping the use-case pipeline, and specifying the architecture required to deliver prioritized initiatives.
Provide expertise on responsible AI, privacy, and risk-aware design.
Communicate complex concepts to stakeholders at all levels.
Mentor engineers and data scientists on architecture, quality, and emerging AI capabilities.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field. OR equivalent work experience.
• Additional certifications in AI/ML technologies are preferred.
• Strong understanding of security, privacy, compliance, and responsible AI principles, including access control, data protection, and risk mitigation.
• Deep understanding of machine learning, generative AI, LLMs, RAG, prompt engineering, vector databases, and model evaluation frameworks.
• Experience translating business requirements into solution architectures, technical roadmaps, and implementation plans.
• Experience working cross-functionally with engineering, product, data teams, and business stakeholders to deliver measurable outcomes.
• Knowledge of MLOps/LLMOps practices such as CI/CD, model monitoring, observability, versioning, governance, and lifecycle management.
• Exceptionally curious, adaptive, and proactive, stays ahead of fast-changing AI technologies.
• Fast learner with ability to shift between conceptual and hands-on tasks.
• Strong problem solver with a “builder” mentality.
• Comfortable with ambiguity, rapid experimentation, and iterative design.
• Excellent communicator to both technical and business audiences.
• Collaborative and supportive partner to cross-functional teams.

Pay

The estimated salary range for this position is $150,000 to $175,000 plus bonus. Starting pay is dependent on multiple factors, such as skills, experience, and work location, and is not typically at the top of the range.

Benefits

• Full benefits package including Flexible Time Off (FTO), health, dental, vision, investment savings plan, bonus, equity incentive, and additional miscellaneous benefits.