AI Engineer

Zenith Insurance Company•Los Angeles, CA

1d•Hybrid

About The Position

Zenith is a team of Workers' Compensation Specialists committed to helping businesses succeed by protecting against the financial and human consequences of workplace injuries, providing for the needs of injured employees and making the workplace safer. The company values collaboration, work-life balance, and integrity, and supports career advancement through a dedication to ongoing learning and development. An individual coming to Zenith will receive competitive compensation, a comprehensive benefits package, and continuous opportunities to grow as a professional. Zenith is expanding its AI team as it embarks on a major digital transformation. As part of the AI Center of Excellence, the AI Engineer will work alongside industry-leading peers to build AI systems that have direct enterprise-wide impact, with access to the latest technology and a clear organizational commitment. This is a ground-floor opportunity on a team and initiative that is just getting started. Under general supervision, the role involves designing and building production-grade AI systems for core business use cases, developing LLM-powered applications, retrieval pipelines, and agentic workflows from design through deployment. The AI Engineer will execute the complete life cycle for moderately complex AI system components in collaboration with business, product, and data stakeholders.

Requirements

High School Diploma or equivalent combination of training/experience required
Bachelor’s Degree or equivalent combination of training/experience required
3-5 years of related software engineering or data science experience with meaningful time building AI systems required.
Solid Python and SQL fundamentals; comfortable with API design (FastAPI/REST) and cloud deployments (Azure, AWS, GCP); expert IDE and notebook-based development.
Hands-on experience building and deploying LLM applications in production (OpenAI, Anthropic, Gemini, or equivalent APIs).
Proficiency with RAG architectures, vector databases (Pinecone, Weaviate, pgvector, Azure AI Search), vector search optimizations, and embedding workflows.
Experience with agentic frameworks and tool-use/function-calling patterns (LangChain, LangGraph, LlamaIndex, or custom orchestration).
Strong analytical and problem solving skills applied to complex, ambiguous AI system design challenges.
Excellent written and verbal communication skills; ability to work across technical and non-technical teams, stakeholders, and decision makers.
Team player, self-starter, motivated, problem solving mentality.
Ability to focus and prioritize work requirements, strong strategic and tactical mindset.
Stays current and evaluates latest emerging AI/ML technology for incorporation in AI solutions.

Nice To Haves

Masters degree preferred
Data science or machine learning background (scikit-learn, XGBoost, PyTorch) - Preferred.
Familiarity with insurance, underwriting, or financial services domains - Preferred.
Familiarity with data platforms like Databricks or Snowflake - Preferred.
Familiarity with ethical AI best practices, and AI and data regulatory fundamentals - Preferred.

Responsibilities

Understand assignments and work independently for extended periods on AI system design and implementation tasks.
Design, build, and maintain LLM-powered applications for business workflows including risk summarization, document extraction, and decision-support tools.
Architect and maintain RAG pipelines, vector stores, and retrieval systems grounded in enterprise data.
Develop and orchestrate multi-step agentic systems using frameworks such as LangChain, LlamaIndex, or custom toolchains.
Define and run evaluation frameworks to measure output quality, reliability, and safety of AI systems in production, and instrument prompts, model calls, and system traces for observability and continuous improvement.
Collaborate with subject matter experts to iterate on system behavior, feedback loops, and edge case handling.
Work productively and harmoniously with others on a consistent basis.
Respond positively to direction and feedback on performance.
Consistently maintain professional and appropriate demeanor.
Perform other duties/projects as assigned.