We are seeking a
Lead AI Engineer to serve as our organization's foremost technical authority on artificial intelligence strategy, architecture, and adoption. At Veracity, that means shaping how AI is built and scaled across a customer-facing digital insurance platform serving small business owners nationwide - from how we surface coverage recommendations to how we prepare for a world where AI agents increasingly research and purchase insurance on behalf of human customers.
This is not a people management role - it is a systems leadership role. You will act as the connective tissue between engineering, product, and business leadership, making and owning the high-stakes technical decisions: build vs. buy, platform selection, architectural patterns, and AI tooling standards. You will bring structure and discipline to our AI practice while operating with the urgency and adaptability of a fast-moving, independent company.
Key ResponsibilitiesTechnical Strategy & Direction- Define the AI engineering roadmap and architecture standards across the organization
- Lead build vs. buy vs. integrate decision-making for AI systems and platforms - and be accountable for articulating how you arrived at those decisions
- Evaluate emerging tools, frameworks, and models; provide clear, defensible recommendations to leadership
- Serve as the ultimate technical escalation point for complex AI/ML system design challenges
Enterprise Systems & Scaling- Architect AI solutions for our enterprise platform - which is actively being upgraded and requires someone comfortable working across both the process layer and the underlying platform architecture as a normal part of the role, not just layering AI on top of stable infrastructure
- Design systems for scale, reliability, and cost-efficiency in production environments
- Establish LLMOps practices - evaluation and regression suites for LLM-powered features, cost and quality observability, versioned prompts and configs with staged rollout and rollback, and production guardrails
- Ensure AI systems integrate cleanly with existing product and engineering infrastructure
Cross-Functional Collaboration- Partner closely with Product and Engineering leadership to align AI capabilities with business outcomes
- Receive operational support to help initiate and coordinate cross-functional engagement, allowing you to stay focused on technical leadership and decision-making
- Provide clear guidance on resource allocation - who owns what, who should be engaged, and in what sequence
- Translate complex technical concepts for non-technical audiences, including executives and business stakeholders
- Challenge direction constructively and push back on approaches that compromise long-term system health
AI Coding & Process Transformation- Champion and introduce AI-assisted coding practices and developer tooling across the engineering organization
- Define standards for responsible AI development including guardrails, evaluation frameworks, and security considerations
- Drive continuous improvement in how the organization builds and ships AI-powered features
Requirements and QualificationsRequired- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience
- 5+ years of software engineering experience with a meaningful portion in production AI/ML or LLM/GenAI systems - strong judgment and vision at the 5-6 year mark will not be screened out on tenure alone
- 2+ years building production LLM/GenAI and agentic systems, plus fluency with AI-assisted coding tooling and the judgment to set org-wide standards, evals, and guardrails for AI-generated code
- Demonstrated track record of taking an existing business process apart and rebuilding it with AI at the core within an existing enterprise environment - shipped to production and owned the outcome
- Production experience with LLM/GenAI and agentic systems - agent orchestration, tool calling, RAG, structured outputs - with the fluency to set org-wide standards, evals, and guardrails for AI-generated code
- Sound judgment about where AI belongs and where it must not - comfortable with probabilistic agents for customer-facing and research tasks, while treating policy binding, money movement, and compliance flows as deterministic, auditable, and human-governed; this framing is non-negotiable in an insurance context
- Experience making and communicating build vs. buy vs. integrate decisions at an organizational level
- Proficiency in Python and the modern GenAI application stack - agent and orchestration frameworks, model-provider SDKs, vector databases, and evaluation tooling; screened for fluency with the stack generally, not a specific checklist of tools
- Exceptional written and verbal communication skills - you can write a crisp architecture decision record and present it to a board-level audience
Preferred- Direct evidence of legacy-process redesign with real latitude to alter underlying platform architecture - not just process work layered on top of stable infrastructure
- Enterprise or regulated-domain experience, ideally in a business context closer to insurance or financial services
- Experience in a technical lead or principal engineer role with broad organizational influence
- Background working closely with product engineering teams in a dual-track agile model
- Experience with AI cost management, observability, and governance frameworks
Perks- Health, dental, and vision plans
- Amazing work-life balance with 4 weeks of Paid Time Off
- 10 Paid Company Holidays with 2 floating holidays
- 401K Programs with employer match
- Personal assistance programs for support in a healthy personal and work life
Compensation Range:$200k/yr - $220k/yr + 10% Bonus
