Engineering Manager - Agentic AI
Sydney, New South Wales, Australia · Full Time
Be the first to apply
- Experience
- 7+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 2 రోజులు క్రితం
- Work mode
- In office
- Resume
- Required to apply
Where you'll work
Sign in to tell us what does and doesn't work for you here — it sharpens every match we show you.
Job description
About Cover Genius
Cover Genius serves as the global platform for embedded insurance protection, operating in over 60 countries and all 50 U.S. states. We safeguard the customers of major digital companies including Klarna, Revolut, Stripe, Priceline, Agoda, Booking.com, Turkish Airlines, Tongcheng Travel, eBay, and Uber through seamless, end-to-end service. To date, we have protected more than 73 million customers worldwide, managing 240 million policies with USD 3.2 billion in gross written sales.
Following a year marked by 40% year-over-year revenue growth and a recent $100 million capital injection that values us at $1.9 billion, we are accelerating growth further. By joining us, you'll contribute to advancing our AI-first vision by developing hyper-personalized tech, agentic distribution systems, and automated claims solutions to support the expanding $70 billion embedded protection market.
Role Summary
We are looking for a hands-on Engineering Manager specializing in Agentic AI to lead and expand our team responsible for next-generation AI-driven business platforms. This leadership role requires deep technical expertise to shape strategies for applying Large Language Models (LLMs) and deep learning to practical business challenges. You will oversee a team engineering AI solutions that are secure, scalable, and production-ready, ensuring robust and cost-efficient AI infrastructure across deployments.
Key Responsibilities
- Guide and develop a multi-disciplinary team of AI and software engineers, promoting a culture of high technical standards, psychological safety, and innovation through rapid experimentation.
- Design and develop AI-native services from prototypes to full production, including sophisticated Retrieval-Augmented Generation (RAG) pipelines and orchestration of agents supporting multilingual capabilities and product distribution.
- Implement best practices around Generative AI, MLOps, covering prompt management, model deployment, cost control, and responsible AI governance.
- Engage actively in code reviews, architectural planning, and design documentation; capable of stepping into the codebase to resolve critical problems when necessary.
- Act as the crucial liaison between Product and Engineering teams, effectively communicating the strengths and limits of current deep learning and GenAI models.
Required Qualifications and Skills
- Minimum 7 years of software engineering experience with a strong background in Python backend development, plus over 2 years managing engineering teams involving mentorship and shipping products.
- Proven experience bringing LLM-based products from concept through deployment, including handling evaluations, safety measures, performance budgets, incident management, and iteration based on user feedback.
- Technical expertise in agentic systems, multi-step processes, RAG, tool integration, and memory management within AI systems.
- Experience in building data analytics and insights products that convert complex operational data into actionable intelligence or intuitive natural language tools for non-technical users.
- Comprehensive knowledge of the modern AI ecosystem – agent frameworks, vector databases, model APIs, open-weight models, and Kubernetes orchestration.
- Strong foundational understanding of LLMs, including transformer architectures, embeddings, and fine-tuning trade-offs to guide the team beyond hype to practical application.
- Experience ensuring production service SLAs, uptime reliability, and managing incident response for critical systems.
Personal Attributes
- Pragmatic mindset recognizing that AI is not a universal solution, favoring simple, durable engineering over hype-driven approaches.
- A self-directed learner passionate about continuously updating skills in data engineering and AI tooling.
- Discipline in skepticism: critically analyzing model outputs, probing assumptions, identifying biases and failure modes, and prioritizing thorough evaluations before feature development.
- Embodies company values such as bold experimentation, purposeful innovation, and authentic collaboration across diverse global teams.
- Strong analytical ability to translate business problems into AI challenges, critically reviewing model results and assumptions.
Why Join Us?
At Cover Genius, we transform one of the oldest, most complex industries through top-tier technology, making insurance seamless and extraordinary. Our guiding principles include urgency, accountability, collective growth, inspiration, and customer-centric innovation. We foster a work environment of trust, challenge, and empowerment.
Legal and Privacy
Cover Genius is committed to diversity and inclusion, prohibiting discrimination on any legally protected grounds. By applying, you consent to personal data processing for recruitment purposes, acknowledging potential AI-assisted application assessments; however, final hiring decisions remain human-led. Applicant data is retained for three years per our Privacy Policy.