AI Solutions Architect

eNGINE builds Technical Teams. We are a Solutions and Placement firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build. Our Consulting Workforce is encouraged to enjoy career fulfillment in the form of challenging projects, schedule flexibility, and paid training/certifications. Successful outcomes start and finish with eNGINE., eNGINE is looking for an AI Solutions Architect to design and steer how AI actually gets used across the business - not chasing trends, but figuring out where it genuinely creates value and building a practical path to get there. This role sits at the intersection of technical architecture and business strategy: you’re the person who can walk into a room with vague ideas about “using AI for X” and walk out with a scoped, feasible plan.

This isn’t a heavy coding role, but it’s not a purely strategy role either. You’ll need real technical judgment - a solid grasp of when to use AI agents, LLM-driven automation, computer vision, or plain traditional ML, and just as importantly, when none of those are the right call. Part of the job is having the credibility to push back when an idea sounds exciting but won’t hold up in production.

You’ll also own the applied AI roadmap - deciding what gets built now, what gets built later, and how you’ll know if it worked. A small team (1-5 people - AI developers, data engineers, or analysts) will report to you.

What You’ll Own

• Partnering with business leaders to translate fuzzy problems into well-scoped AI initiatives
• Architecting solutions using the right approach for the job - agents/copilots, LLM reasoning and automation, computer vision, or traditional ML
• Building and maintaining the AI roadmap, balancing near-term wins against longer-term capability building
• Making sure AI initiatives are coordinated and prioritized as part of one program, not scattered one-off experiments
• Defining success metrics before a project kicks off, not after it ships
• Leading a small technical team without needing to be the one writing production code
• Owning the practical realities of running AI in production: cost, security, data privacy, responsible AI practices, and monitoring adoption and effectiveness

• 6+ years of experience, with at least 3 years in a technical leadership, architecture, or product capacity
• Bachelor’s degree in computer information systems or a related field - or equivalent hands-on experience in AI, ML, and analytics
• Strong, recent experience architecting solutions on Azure, Microsoft Fabric, and Power Platform
• Deep experience with AI-driven customer service solutions
• A track record of leading AI or data initiatives end-to-end in a cloud environment - including ROI measurement, cost optimization, security, and governance
• Comfort explaining architectural tradeoffs to executive stakeholders, and the ability to influence decisions without formal authority
• Strong grounding in traditional ML concepts (training, inference, evaluation, drift) and working knowledge of computer vision where relevant
• Experience building roadmaps, setting success metrics up front, and weighing value against feasibility and risk
• Familiarity with the Microsoft AI ecosystem - Fabric, Copilot Studio, Power Automate, and Azure’s data/AI services at an architectural level
• Ability to guide technical teams and external partners effectively without writing production code day-to-day

Pulled from the full job description

• Paid training
• 401(k)
• Health insurance
• 401(k) matching
• Paid time off
• Vision insurance
• Health savings account, * 401(k)
• 401(k) matching
• Dental insurance
• Health insurance
• Health savings account
• Paid time off
• Vision insurance