AI Architect

90 billion by 2025. As a key player in the industry, Accelerize 360 is seeking an experienced AI Architect to drive their AI practice forward. With the rise of remote work, digital skills are more crucial than ever, and candidates with a strong background in software engineering and AI/ML systems are in high demand. Before applying, candidates should be aware of the company's focus on delivering under fixed timelines and the need for hands-on architecture experience.

About the Role

As an AI Architect at Accelerize 360, you will be responsible for translating strategic direction into production-ready AI solutions. This involves scoping the right architecture, owning the technical design, and ensuring that engineering teams execute with precision and consistency. You will work across multiple client engagements, partnering closely with an AI Advisor to deliver end-to-end solutions.

The AI Architect role is a key component of Accelerize 360's AI practice, and you will be expected to bring a deep understanding of AI/ML systems, LLMs, and cloud platforms to the table. Your expertise will inform the development of production-ready AI solutions, and you will be responsible for ensuring that these solutions meet the highest standards of quality and reliability.

In this role, you will have the opportunity to work with a talented team of engineers and AI professionals, and you will be expected to contribute to the development of internal IP, including reusable patterns, accelerators, and architecture frameworks.

What You Will Do

• Design end-to-end AI solution architectures, including model selection, data pipelines, orchestration layers, integration points, and deployment infrastructure
• Build rapid prototypes that make AI concepts tangible for clients, driving decisions and informing the real build
• Translate business requirements and AI strategy into implementation-ready technical specifications
• Evaluate and recommend the right components of the AI stack, including LLMs, vector databases, and fine-tuning approaches
• Define and enforce architecture standards across the delivery team, catching design mistakes before they become production problems
• Lead technical discovery with clients, assessing existing data infrastructure, identifying gaps, and sizing the build effort honestly
• Act as the senior technical voice in client-facing conversations, communicating complexity clearly and effectively
• Review and guide the work of AI engineers, flagging architectural drift early and course-correcting without creating bottlenecks
• Contribute to internal IP, including reusable patterns, accelerators, and architecture frameworks
• Collaborate with cross-functional teams to ensure successful delivery of AI solutions
• Stay up-to-date with industry trends and advancements in AI/ML, applying this knowledge to drive innovation and improvement

What We Are Looking For

• 7+ years of experience in software or data engineering, with at least 3 years in a hands-on architecture role
• Consulting or professional services background, with experience delivering under fixed timelines
• Deep fluency in designing and deploying production AI/ML systems, including LLMs and cloud platforms
• Practical experience with LLM application patterns, including RAG, agents, function calling, and prompt engineering at scale
• Strong command of at least one major cloud platform, including AI/ML services such as SageMaker, Azure ML, or Vertex AI
• Hands-on experience with LLM orchestration frameworks, vector databases, and model serving infrastructure
• Proficiency in Python and comfort across the modern data stack, including dbt, Airflow, and Snowflake
• Ability to write and review code, with a focus on readability and maintainability
• Experience operating in ambiguous, client-facing environments with evolving requirements and trade-offs
• Strong communication and interpersonal skills, with the ability to work effectively with clients and cross-functional teams

Nice to Have

• Experience with containerization and orchestration using Docker and Kubernetes
• Familiarity with agile development methodologies and version control systems such as Git
• Knowledge of data governance and security best practices, including data encryption and access controls
• Experience with cloud-based data platforms, including AWS, Azure, or Google Cloud
• Certification in AI/ML or a related field, such as AWS Certified Machine Learning or Google Cloud Certified - Professional Data Engineer

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work with a talented team of AI professionals and engineers
• Collaborative and dynamic work environment
• Flexible working hours and remote work options
• Professional development opportunities, including training and certification programs
• Access to cutting-edge technologies and tools, including AI/ML platforms and cloud services
• Recognition and reward for outstanding performance and contributions
• Comprehensive health and wellness programs, including mental health support and employee assistance
• Generous paid time off and holiday schedule

• Develop a strong portfolio that showcases your experience in designing and deploying production AI/ML systems, including LLMs and cloud platforms.
• Be prepared to discuss your approach to architecture and design, including your experience with LLM application patterns and cloud services.
• Highlight your ability to communicate complex technical concepts to non-technical stakeholders, including clients and cross-functional teams.
• Emphasize your experience working in ambiguous, client-facing environments with evolving requirements and trade-offs.
• Prepare to discuss your experience with agile development methodologies and version control systems, as well as your ability to write and review code.
• Be ready to discuss your knowledge of data governance and security best practices, including data encryption and access controls.
• Show your passion for AI and machine learning, and highlight your commitment to ongoing learning and professional development.