Note: The job is a remote job and is open to candidates in USA. Veracity Insurance Solutions, LLC is an independent insurance partner serving small business owners through a digital insurance platform. The Lead AI Engineer will define the organization’s AI strategy and architecture, lead major technical decisions, and establish scalable production practices for AI/ML and LLM-powered systems. The role also partners with product and engineering leadership, introduces AI-assisted development standards, and drives AI-focused process transformation.
Responsibilities
- 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
- 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
- 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
- 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
Skills
- 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
- 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
Benefits
- 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
Company Overview
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