Lead AI Engineer
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Job Description
Lead AI Engineer at InsCipher creating AI solutions for digital insurance platform. Shaping enterprise AI strategies and collaborating cross-functionally to enhance customer outcomes.
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
- Design systems for scale, reliability, and cost-efficiency in production environments
- Establish LLMOps practices
- 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
- Provide clear guidance on resource allocation
- Translate complex technical concepts for non-technical audiences
- 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:
- 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.
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
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