Note: The job is a remote job and is open to candidates in USA. InsCipher provides compliance solutions for surplus lines brokers, state departments of insurance, and associations through tax filing, reporting, and regulatory workflow automation. The Lead AI Engineer will define the organization’s AI strategy and architecture, guide build-versus-buy decisions, and serve as the technical authority for AI/ML systems. The role will also scale production AI capabilities, establish LLMOps and governance practices, and lead AI-assisted coding and process transformation across engineering.
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
- Required to perform other duties as requested, directed, or assigned
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
- 10% Bonus
- Work on cutting-edge projects that are reshaping an industry
- Collaborate with a team of passionate, like-minded professionals
- Enjoy a culture that values flexibility, innovation, and personal growth
Company Overview