Staff Applied AI Engineer - Kalepa for Underwriting

Kalepa

10h • $243,000 - $345,000 • Remote

About The Position

Kalepa is seeking a Staff Applied AI Engineer to set the technical direction for turning unstructured insurance data into structured, explainable facts at scale. The role owns the architecture of LLM-based extraction, classification, and matching systems, the evaluation infrastructure that governs them, and the model strategy—including decisions about approaches, models, and vendors.

The engineer will work across product, engineering, data science, and business leadership to connect model outputs to customer value. The team owns Kalepa’s proprietary risk representation layer and intelligent model-driven insights, converting past submissions and syncs into a durable data moat. Its ownership areas include risk representation, the winnability model, and future models such as loss prediction and portfolio optimizers.

Kalepa is primarily remote, with employees across the US, Canada, and Europe and headquarters in New York City. The role’s listed North America salary ranges are $270,000–$345,000 for Zone 1 (New York and San Francisco) and $243,000–$310,500 for Zone 2 (other US and Canadian locations). Final compensation depends on relevant experience, interview performance, and geographic location.

Requirements

• At least 8 years of engineering experience, including at least 5 years building and operating ML or LLM systems in production.
• Experience serving as technical lead for at least one major applied AI initiative or product.
• Deep expertise in LLM-based systems, including structured extraction, classification, retrieval and embeddings, evaluation, and reliable, economical operation at scale.
• Mastery of applied machine learning, NLP, and statistics, and of Python and its data and ML libraries.
• Experience with AWS and serverless technologies such as Lambda and EC2, asynchronous workflows, and cloud environments.
• Established record as a go-to technical resource for engineering, product, and business staff.
• Ability to take full ownership of work and drive initiatives to completion with minimal oversight.
• Ability to communicate proactively and persuasively with engineers, product teams, and leadership.
• Comfort with experimentation and interest in challenging problems.

Nice To Haves

• Experience with document AI at scale, including OCR, layout understanding, and long-document or multi-page extraction.
• Experience fine-tuning or distilling models for production use.
• Experience building evaluation platforms or ML infrastructure used by other teams.
• Familiarity with insurance, underwriting, or submission documents such as ACORD forms and loss runs.

Responsibilities

• Lead the technical, data, and project aspects of applied AI initiatives, including document extraction, classification, entity matching, and the evaluation platform.
• Set technical direction for building and operating LLM-based systems at scale, balancing accuracy, cost, latency, reliability, and explainability.
• Lead architectural decisions across data science and backend systems and provide strong systems design.
• Own evaluation infrastructure, including benchmark datasets, regression suites, validation strategies, and standards that model changes must meet before release.
• Deliver major product and data science innovations in each release and tie model outputs to customer value.
• Lead model and vendor strategy, including decisions about adopting new models, fine-tuning models, and replacing pipelines.
• Partner with product and business owners to drive firm-wide decisions while weighing data, resources, and tradeoffs.
• Proactively manage technical debt across the AI stack, lead code reviews, and promote development and deployment best practices.
• Represent Kalepa internally and externally, including through recruiting and training.
• Use AI tooling deliberately to increase personal and team impact.

Benefits

• Significant equity options package.
• 20 days of PTO per year.
• Global team offsites.
• Healthy living/gym stipend.
• Mobile phone bill stipend.
• Continuing education credits.
• For US employees: 100% covered medical, vision, and dental insurance for individuals and families.
• For US employees: 401(k) plan with employer contribution, regardless of employee contribution.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed