Engineering Manager - Agentic AI

About the Company  

Cover Genius is the global infrastructure for embedded protection. Active in over 60 countries and all 50 US States, we protect the customers of the world’s largest digital companies, including Klarna, Revolut, Stripe, Priceline, Agoda, Booking.com, Turkish Airlines, Tongcheng Travel, eBay, and Uber, with seamless, end-to-end experiences. Cover Genius has protected more than 73M customers globally across 240M policies with USD $3.2BN in gross written sales. 

Coming off a stellar year with 40% YoY revenue growth and a recent $100M capital raise, putting our valuation at $1.9BN, we are accelerating into our next phase of growth. As part of our team, you’ll help drive our AI-first roadmap, developing hyper-personalization engines, agentic distribution, and automated claims infrastructure, while building the scalable technology powering the fast-growing $70B embedded protection market.

Our people are: Accountable, customer-obsessed, collaborative, driven

Our people are not: Passive, defensive, siloed, hesitant

About the Role

We’re seeking a hands-on Engineering Manager - Agentic AI to lead and grow the team building our next-generation AI-powered business platforms.

This is a high-impact role for a leader who is technically deep. You will not just manage people; you will drive the technical strategy for how we apply Large Language Models (LLMs) and Deep Learning to real-world business problems. You will lead a team of engineers in leveraging a diverse suite of AI technologies to architect secure, production-grade solutions that solve complex business challenges. You will ensure our underlying AI infrastructure remains scalable, robust, and cost-optimized across all deployments.

Key Responsibilities:

• Mentor and grow a cross-functional team of AI and software engineers.  Foster a culture of technical excellence, psychological safety, and rapid experimentation.

• Architect and build AI-native services, moving from prototype to production, including designing advanced RAG (Retrieval-Augmented Generation) pipelines and orchestrating agents for multilingual support and product distribution.

• Establish best practices for GenAI, MLOps, including Prompt management, model deployment, cost management, responsible AI and so on.

• Actively participate in code reviews, design docs, and architectural discussions. While you won't write code every day, you are capable of diving into the codebase to unblock the team or fix critical issues.

• Serve as the bridge between Product and Engineering, clearly communicating the capabilities and limitations of current deep learning models and GenAI technologies.

Skills & Experience:

What you will have

• 7+ years software engineering experience with Python backends, including 2+ years leading engineers as a manager that growing people while shipping

• You've taken LLM-powered products from prototype to production and lived with them afterwards: evals, guardrails, cost and latency budgets, incident response, and iterating on real user feedback

• Hands-on depth in agentic systems, tool use, multi-step orchestration, RAG, and memory.

• Experience building data and insights products: turning messy operational data into analytics, decision support, or natural-language interfaces that non-technical teams actually use.

• Fluency across the modern AI stack (agent frameworks, vector stores, model APIs and open-weight models, Kubernetes)

• Strong grasp of LLM fundamentals — transformers, embeddings, fine-tuning trade-offs — so you can steer the team past hype toward techniques that work.

• Experience managing SLAs, uptime, and incident response for critical production services.

What you will bring

• You know that AI isn't the solution to every problem. You prioritize simple, robust engineering over hype.

• You are self-motivated and continuously study the new practices and tooling in data engineering.

• Skepticism as a discipline: you critically evaluate model outputs, question assumptions, probe for bias and failure modes, and build evals before you build features.

  Embodies CG values—bold experimentation, purposeful innovation and authentic collaboration across diverse, global teams. 

• The ability to analyze business problems and frame it for AI, critically evaluating model outputs, questioning assumptions and identifying potential biases.

Why Cover Genius?  

At Cover Genius, we create magic by turning the archaic into the extraordinary. We take one of the world’s oldest and most complex industries and reinvent it with world-class technology. Cover Genius doesn’t just disrupt legacy insurance; we make the impossible feel effortless.Our operating principles guide our mission: 

• Make today matter: We deliver with urgency and excellence. We act decisively, move with intention, and hold a high bar.

• Act with accountability: We own our commitments  and take pride in delivering results that move us forward.

• Grow together: We are a collective of curious minds. We learn from wins and setbacks, share knowledge generously, and elevate each other every day.

• Inspire Each Other: We push each other to think bigger and pull together to go further.

• Champion Our Customers: We lead with empathy and center the customer, turning complex disruptions into seamless moments of trust.

• Don't just take our word for it- hear about our culture straight from our people here: story time

Ready to make an impact? If you’re looking for a place where you’ll be challenged, trusted, and empowered, we’d love to meet you.

The Legal & Privacy Stuff

Cover Genius promotes diversity and inclusivity. We don't tolerate discrimination, demeaning treatment of anyone, or harassment due to race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status.

By submitting your application, you acknowledge that we may collect, store, and process your personal data for recruitment purposes. To ensure a fair evaluation, we may use AI to assist in sorting applications, but all final decisions are made by our hiring team and no candidate dispositions are automated. We will keep your information on file for three years from the date of your application. For detailed information about how we handle your data and our use of AI, please review our full .