Founding AI Software Engineer | Nolana AI · Teeming.ai
Nolana AI
Nolana automates and accelerates candidate screening calls so talent teams can evaluate and progress many more applicants in minutes. It is a B2B SaaS platform that uses AI and generative models with…
Nolana automates and accelerates candidate screening calls so talent teams can evaluate and progress many more applicants in minutes. It is a B2B SaaS platform that uses AI and generative models with…
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Company Description
We are building an AI-native, agentic operating system designed to automate complex insurance operations — from dynamic First Notice of Loss (FNOL) intake to automated claims lifecycle management and customer service. We are moving beyond simple chatbots to create true AI agents that can reason, plan, and execute multi-step workflows while keeping humans in control. If you are passionate about applied generative AI and want to modernise the insurance industry, we want you on our team.
Role Description
We are looking for a highly skilled AI Full Stack Engineer to help us architect and scale our agentic workflows. In this role, you will bridge the gap between cutting-edge generative AI models and robust, production-ready web applications. You will work across the entire stack, utilising the latest frameworks to build intelligent modules, robust retrieval pipelines, and real-time voice interfaces that safely and securely automate insurance processes.
This is a full-time hybrid role located in the iconic Lloyd's of London building in London, with the flexibility to work from home 2 days a week. As the Founding AI Software Engineer, you will design, implement, and optimise AI software solutions for insurance automation.
Qualifications
Robust background in Computer Science and Software Development
Good understanding of Pattern Recognition, and Natural Language Processing (NLP)
Experience with scalable and secure software solutions
Ability to work both independently and collaboratively in a hybrid work environment
Familiarity with integrating AI models into existing systems is a plus
Bachelor’s degree in Computer Science or a related field; advanced degrees are a bonus
Key Responsibilities
What We’re Looking For
Benefits & Perks
Hybrid Flexibility:
Work alongside a collaborative team 3 days a week in our London office at the iconic Lloyd’s of London building.
Health & Wellness:
Gym subscription and unlimited holidays.
Commuter Friendly:
Cycle to work scheme available.
Growth:
Work at the frontier of agentic AI and voice technology within a fast-growing startup.
Agentic AI Development:
Design, build, and deploy agentic architectures capable of reasoning, utilisng tools, and executing complex workflows for insurance use cases.
Retrieval-Augmented Generation (RAG):
Architect and optimise high-accuracy RAG pipelines to effectively query, ingest, and ground models in complex insurance documentation and policies.
Real-Time Voice AI:
Build low-latency, conversational voice agents and streaming audio interfaces leveraging
LiveKit
and
WebRTC
.
Evals:
Evaluate accuracy and build pipelines in place to do this at scale.
Full Stack Engineering:
Develop scalable front-end and back-end systems using
Next.js
.
AI Integration:
Leverage the
Vercel AI SDK
to integrate the latest Large Language Models (LLMs) and orchestrate dynamic AI interactions.
Background Processing:
Manage reliable, high-throughput asynchronous task queues and job scheduling using
BullMQ
.
Database Architecture:
Design and optimise relational database schemas using
PostgreSQL
to handle complex insurance data securely.
Deep Understanding of Generative AI:
You are up-to-date with the latest models, prompting techniques, and advanced RAG methodologies (e.g., semantic search, chunking strategies, vector databases).
Agentic Architecture Expertise:
Familiarity with the paradigms of AI agents—including memory management, reasoning loops (like ReAct), and tool/function calling.
Tech Stack Proficiency:
Proven experience shipping production applications using
Next.js
,
PostgreSQL
, and
BullMQ
.
Voice & Streaming Experience:
Hands-on experience or a strong technical understanding of
WebRTC
,
LiveKit
, or similar real-time communication protocols.
Ecosystem Knowledge:
Hands-on experience with the
Vercel AI SDK
(strongly preferred) or similar frameworks for building scalable AI applications.
Problem Solver:
Ability to navigate the non-deterministic nature of AI and build reliable, auditable, and secure systems around it.
