AI Technical Lead

Company: VeilSun, Inc.
Employment Type: Full-Time
FLSA Status: Exempt
Pay Type: Salary, Exempt. $115,000 - $140,000 annual base salary, depending on experience
Work Location: Remote. Applicants must be authorized to work in the United States without sponsorship. This position is open only to candidates currently residing in the United States.
Travel Requirement: Occasional travel for all-team meetings and client workshops
AI Technical Lead
Purpose of this Position
The AI Technical Lead is a seasoned AI practitioner and trusted client consultant who serves as the senior technical voice of VeilSun’s AI Practice. This role is consultant first. Before a model is selected or an integration is built, the Technical Lead has done the harder and more important work. They have learned the client’s business, their data, and their goals, and achieved Radical Alignment on what AI should accomplish and why. Radical Alignment is genuine, documented agreement with the client on what is being built, why it is being built, and what success looks like before development begins.
This role combines hands-on AI engineering depth with the consultative presence to guide enterprise AI roadmaps and AI service package engagements. Their expertise goes well beyond third-party AI tools. It includes models, APIs, MCP servers, and the work of connecting AI securely to client data and schemas.
The AI Technical Lead also carries an internal mandate. They redesign how VeilSun delivers, prove on real projects that AI can compress weeks of technical work into days, and build AI capability across the delivery organization. Low code moves the work. AI makes it intelligent. This role makes that promise real for our clients and keeps VeilSun’s low-code practices competitive and growing.
Business Outcomes
Success in this role means AI engagements deliver measurable client value, VeilSun delivers faster with leaner teams, and AI capability is spreading across the delivery organization. You will be measured on:
Engagement quality. AI roadmaps and service package engagements are technically sound, right-sized, and tied to client business outcomes.
Client satisfaction. Clients feel heard, informed, and confident. Risks around data, security, and model behavior are surfaced early and worked through together.
Acceleration results. Complex work such as data mapping and code generation moves from weeks or months to days. Results are measured, documented, and repeatable.
Team enablement. Delivery team members, including PMs and leadership, show measurable growth in AI skills and day-to-day adoption.
Knowledge distribution. AI expertise is held by multiple team members, not one person.
Commercial discipline. Meets the billable utilization target agreed with AI Practice leadership. Estimates are accurate and margin is protected.
Core Responsibilities
Enterprise AI Roadmapping & Client Consulting
Serve as the technical expert on enterprise AI roadmap and AI service package engagements, partnering with the AI Services Lead and the project lead.
Lead discovery with discipline. Learn the client’s business, data landscape, and systems before recommending an AI approach.
Achieve Radical Alignment on AI use cases, success measures, and boundaries before any build begins.
Translate AI possibilities into practical, phased roadmaps that deliver value in small, high-value increments.
Advise clients candidly on what AI can and cannot do today. Redirect them away from poorly fit use cases, unsafe data practices, or oversized investments.
Educate client stakeholders on tradeoffs among cost, accuracy, security, and speed so they can make informed decisions.
Partner with the Solution Engineer during the handoff from sales so technical design and estimates carry into delivery intact.
AI Engineering & Architecture
Design and build AI solutions that go beyond off-the-shelf tools, including model selection, API integration, prompt and agent design, and MCP server development.
Connect AI to client data and schemas securely, with attention to data quality, access controls, and governance.
Integrate AI capabilities with the Quickbase, Mendix, and custom web applications delivered by VeilSun’s other practices.
Serve as the primary technical authority on assigned AI engagements. Make and defend architecture decisions with confidence.
Establish and document AI development standards, reusable patterns, and evaluation practices for the practice.
Validate AI output quality through testing and evaluation. Keep a human in the loop where the risk calls for it.
Delivery Model Modernization
Redesign VeilSun’s delivery methods so engagements of $400K to $500K can be run by a project lead and one developer, with QA added when needed.
Identify where AI can compress effort across the delivery lifecycle, including requirements, data mapping, code generation, testing, and documentation.
Prove new approaches on real client projects. Measure the results and turn what works into repeatable practice.
Partner with the PMO and Delivery Team Managers to update estimating, staffing, and quality practices to fit the new model.
AI-Accelerated Development
Show the team, on live engagements, how AI cuts complex technical work like data mapping and code generation from weeks or months to days.
Build and share the tools, prompts, workflows, and templates that let other developers repeat those results.
Protect quality while moving faster. AI-generated work is reviewed, tested, and maintainable before it reaches a client.
Internal Initiatives & Platform Depth
Help build and accelerate VeilSun’s internal MCP integration between Claude and Quickbase.
Work with the related work group as testers. Gather feedback, prioritize fixes, and move the integration toward production use.
Learn and build VeilSun’s depth on RapidMiner AI Studio and AI Graph with existing team members so the expertise does not sit with one person.
Apply AI to keep VeilSun’s Quickbase practice competitive and growing through new offerings, faster delivery, and stronger client outcomes.
Team Enablement & Change Leadership
Lead workshops, coaching, and hands-on sessions that build AI skills across delivery, including Developers, PMs, and leadership.
Drive the change toward AI-first thinking about what is technically possible and how long it should take.
Meet people where they are. Tailor enablement to each role and build real confidence, not just awareness.
Mentor Developers through pairing, reviews, and direct coaching on AI-assisted development.
Contribute to the practice’s knowledge base. Document solutions, patterns, and lessons learned in a form others can use.
Risk Identification & Commercial Discipline
Scan engagements continuously for technical, data, security, scope, and client relationship risks. Raise them with enough lead time for the team to act, not react.
Escalate architectural and delivery risks to AI Practice leadership before they become delivery problems.
Balance billable delivery with enablement and internal initiative work deliberately. Meet the utilization target agreed with AI Practice leadership.
Size AI workstreams with practiced accuracy. Recognize when scope expansion warrants a change order and coordinate rather than absorbing it silently.
Business Development Support
Identify new AI use cases and account growth within assigned clients. Coordinate with the Account Manager on growth opportunities.
Support pre-sales efforts including technical discovery, AI readiness assessments, and proof-of-concept development when needed.
Decision Authority
You have authority to:
Make architecture, model, and integration design decisions on assigned AI engagements.
Hold or redirect scope on active engagements, in coordination with the project lead or AI Practice leadership.
Require rework when AI solutions do not meet quality, security, or architectural standards.
Pilot new AI-accelerated delivery methods on assigned engagements, in agreement with the project lead.
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