AI Solutions Engineer

Allegion • Carmel, IN

1d • Hybrid

About The Position

The AI Solutions Engineer is responsible for designing, building, and evaluating managed AI agents that automate and augment work across Allegion. Embedded with teams throughout the business, this role learns their processes firsthand, translates needs into clear requirements and success criteria, and stands up agents that produce consistent, trustworthy results with the right level of human oversight. The role also builds the reusable patterns, templates, and evaluation practices that make each successive agent faster and safer to deliver.

Qualified candidates must be legally authorized to be employed in the United States. The company does not intend to provide sponsorship for employment visa status (e.g., H-1B, TN, etc.) for this employment position.

At Allegion, we are driven by a bold vision: redefining safety while empowering our employees to thrive. When you join our team, you become part of a culture that values innovation, purpose, and excellence. This role offers the benefits of our dynamic hybrid work model—combining in-person collaboration for meaningful moments with the flexibility of remote work. Since hybrid arrangements can vary based on the needs of the individual, team and business, your talent acquisition partner will provide specific hybrid details about this role.

We are committed to fostering a healthy work-life balance and building meaningful connections, ensuring you have the tools, resources, and support needed to excel in any environment. Together, we’ll unlock your potential and create a lasting impact.

While this is the current structure and we currently have no plans to change, we reserve the right to make changes to the hybrid schedule as needed at the Company’s discretion.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.
• 3+ years total experience delivering AI, software, or data solutions, including hands-on work building LLM-based applications or agents.
• Experience designing and building AI agents, including tool use, external system and data integration, and multi-step workflow orchestration.
• Strong proficiency with generative AI and large language models, including prompt engineering for reliable, high-quality outputs.
• Experience defining and implementing evaluations for AI systems that measure quality, consistency, and regression over time.
• Sound judgment on human-in-the-loop design - knowing when oversight is warranted and designing effective review checkpoints.
• Requirements-discovery and facilitation skills - able to embed with a business team, learn an unfamiliar process quickly, and translate it into clear requirements.
• Strong Python proficiency and hands-on experience with cloud platforms; Azure preferred, AWS or GCP acceptable.
• Excellent communication skills, with a proven track record of working effectively with both technical teams and non-technical stakeholders.
• Comfortable establishing new standards and patterns in ambiguous, greenfield territory and refining them with partner teams.
• Ability to work independently and collaborate effectively, in person and remotely.
• Analytical approach to problem-solving, sense of urgency, ability to manage multiple initiatives, and self-direction in keeping current with rapidly changing technology.

Nice To Haves

• Experience with the Model Context Protocol (MCP) or similar frameworks, and with integrating systems of record or CRM platforms (e.g., Microsoft Dynamics), is a plus.
• Experience in a customer-facing, consulting, solutions-engineering, or forward-deployed role is a plus.
• Background in data science, machine learning, or applied statistics, particularly in evaluation or measurement methodology, is a plus.

Responsibilities

• Embedding with teams across Allegion to learn their processes firsthand and identify where an agent will create measurable value.
• Translating unfamiliar business processes into clear agent requirements, scope, and success criteria.
• Designing and building agents that are safe, reliable, and produce consistent outputs.
• Defining what "good" means for each use case and building evaluations that measure accuracy, consistency, and regression over time.
• Deciding where human oversight is warranted - particularly for client-facing outputs or writes to systems of record - and designing those checkpoints in.
• Building reusable patterns, skills, templates, and best practices that standardize agent development across the company.
• Piloting agents with business users and leading acceptance testing before rollout.
• Partnering with data scientists, business partners, and peer AI teams to prioritize use cases and align on delivery.
• Applying responsible-AI practices and staying current with advances in agentic AI and evaluation methods.

Benefits

• Health, dental and vision insurance coverage
• Unlimited Paid Time Off
• 401K plan with a 6% company match and no vesting period
• Health Savings Accounts
• Flexible Spending Accounts
• Disability Insurance –Short-Term and Long-Term coverage
• Life Insurance
• Tuition Reimbursement
• Voluntary Wellness Program
• Employee Discounts through Perks at Work

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level