Lead Data Engineer @Panora (backed by Hexa)
Hexa
ParisPosted about 2 months agoDiscoveredMatch locked
Full TimePanora
About Panora
Panora is building a suite of AI-powered agents for insurance brokers - a highly regulated and operationally complex industry.
Our ambition is to become the
AI Operating System for brokers in Europe
: automating high-friction workflows while improving compliance, advisory quality, and client relationships.
The product is already live with brokerage firms across France and Belgium, with AI assistants in production (quotation automation, contract comparison, coverage analysis, compliance checks, document generation...).
Panora enables brokers to
save hours every week, reduce analysis time by up to 70%, and focus on what truly matters: advising clients
.
Founded by Diane du Paty (ex-VC, operator) and Fabian Langlet (repeat founder, AI product engineer), Panora is backed by Hexa (Aircall, Spendesk, Front).
We are entering a key phase of
scaling and industrializing our AI platform
.
At Panora, AI is not a feature - it is the
core product layer
, deployed in real-world conditions with strong constraints on
reliability, traceability, and compliance
.
Role
We're looking for a
Founding Data Engineer
to help build and scale the systems powering Panora's AI products.
Your work will sit at the intersection of:
•
AI systems
LLMs, agentic workflows, evaluation pipelines, tracing and observability
•
Data engineering
ingestion, normalization, enrichment, extraction and document-processing pipelines
•
Internal datasets
building high-quality, structured insurance datasets from policies, quotes, underwriting questionnaires and business rules
•
Product & backend engineering
designing robust APIs, data models and scalable services used directly in production
•
Insurance expertise
translating real-world insurance workflows, contract language and decision rules into usable data systems
As the third engineering hire, you'll work directly with Fabian (CTO & Co-founder) and Jeremy (Founding Software Engineer), with strong ownership and direct impact on both product and technical direction.
What to Expect
- Join an existing, large-scale codebase and quickly develop a deep understanding of the systems powering Panora.
- Improve, refactor and scale critical parts of the platform while contributing new capabilities where they create the most impact.
- You'll work with complex workflows, unstructured data and real production constraints.
- You'll own problems end-to-end, from AI systems and data pipelines to customer impact.
- Success is measured by product impact, reliability and customer outcomes.
Build & Improve AI Products
- Design, ship and improve AI-powered workflows used daily by insurance brokers
- Build evaluation, feedback and monitoring systems to continuously improve performance
- Turn complex insurance workflows into reliable AI-powered products
Build the Data Foundations
- Build and maintain data pipelines powering our products
- Process and structure unstructured data (contracts, emails, insurer documents)
- Improve the quality, reliability and observability of our systems
Own & Scale Systems
- Own systems end-to-end: from design and implementation to deployment and monitoring
- Contribute to architecture and key technical decisions
- Help define how AI, data and engineering scale at Panora
Our Technology Stack
Built for an AI-first, production-grade product:
•
Languages
Python for AI, data and automation; TypeScript for backend services and product integrations
•
AI systems
LLM-powered agents, structured extraction, evaluation frameworks, tracing, observability and feedback loops
•
Infrastructure
AWS, with a serverless and managed-services approach designed for reliability and scale
•
Data
MongoDB, document-processing pipelines, structured extraction workflows, internal datasets and evaluation datasets
•
Integrations
Microsoft 365, CRM and ERP tools, insurer extranets and other systems used daily by insurance brokers
•
Engineering environment
a large, evolving production codebase: where improving, refactoring and scaling existing systems is as important as building new ones
What matters most is your ability to design robust systems, work with real-world constraints, and learn fast.
What We’re Looking For
We're looking for a builder who ships, enjoys solving difficult problems, and thrives in a small, highly collaborative team.
- Experience building, operating and improving production systems in a startup or product-driven environment
- Experience working closely within an engineering team and contributing to a shared codebase
- Strong Python and backend engineering skills
- Experience with data-intensive products, AI systems, LLM applications or applied machine learning
- Comfortable working with messy, incomplete and unstructured real-world data
- Able to quickly understand, improve and scale existing systems - not just build greenfield projects
- High standards for reliability, data quality, maintainability and customer impact in production
- Comfortable taking ownership, moving quickly and making progress in ambiguous environments
- Strong product mindset: you care about solving meaningful customer problems, not just shipping technical features
Bonus
- Experience with evaluation systems, feedback loops or AI observability
- Experience in fintech, insurance or other regulated environments
⚙️ Recruitment process
•
30min phone screen
with Presci (Talent team)
•
30min interview
with Fabian (Hiring Manager)
•
1h30 technical interview
with Fabian through a peer-programming session
•
30-min interview
with Diane (Co-founder & CEO)
•
Onsite meeting
with a member of the Product / Design team and Mat (Partner at Hexa)
•
Reference checks & offer 🎉
Hexa is committed to creating a diverse environment. All qualified applicants will receive consideration for employment irrespective of gender, origin, identity, background and sexual orientation.
We know there's a long way to go regarding diversity in our industry, which is why we encourage all applicants- especially those listed above- to apply to our open positions.
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Not included in the source posting: what you'll do.
Skills
artificial-intelligencellmpythongomachine-learningawsmongodbserverlesstypescript
Who can apply
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