Lead AI Engineer

InsCipherPleasant Grove, UT
$170,000 - $215,000

About The Position

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.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field (or equivalent practical experience)
  • 8+ years of software engineering experience, with demonstrated mastery designing and shipping production systems where correctness, reliability, and auditability matter
  • 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
  • Sound judgment about where AI belongs and where it must not – comfortable with probabilistic agents for customer-facing and research tasks, while keeping policy binding, money movement, and compliance flows deterministic, auditable, and human-governed
  • Experience making and communicating build vs. buy vs. integrate decisions at an organizational level
  • Proficiency in Python and the modern GenAI application stack – agent/orchestration frameworks (e.g. LangChain, LlamaIndex, or equivalents), model-provider SDKs, vector databases, and evaluation tooling
  • Exceptional written and verbal communication skills – you can write a crisp architecture decision record and present it to a board-level audience

Nice To Haves

  • 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
  • Familiarity with RAG architectures, vector databases, and semantic search at scale
  • Experience with AI cost management, observability, and governance frameworks

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 has already been substantially rebuilt and requires thoughtful evolution, not ground-up construction
  • 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/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

Benefits

  • Health, dental, and vision plans
  • 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
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