What are the responsibilities and job description for the Found Engineer / AI / LLM / position at Motion Recruitment?
A rapidly expanding Insurtech startup is seeking a highly-skilled, passionate and hands-on Founding Engineer to join the team. We're leveraging cutting-edge technologies to transform the insurance industry by streamlining processes, enhancing risk evaluation, and delivering personalized, faster, and smarter experiences for policyholders.
Key Responsibilities
Posted By: Avery Burrell
Key Responsibilities
- Full-Stack Development (35%): Build customer-facing applications across the frontend and backend using technologies such as React, Vue, Node.js, Python, Go, TypeScript, GraphQL, and REST APIs.
- AI/ML Integration & Model Deployment (20%): Work on implementing AI/NLP models and optimizing their performance with frameworks like TensorFlow, PyTorch, Hugging Face, GPT, BERT, FAISS, and Pinecone.
- Cloud & Infrastructure Management (15%): Oversee cloud infrastructure management, ensuring security, reliability, and scalability with AWS, GCP, or Azure.
- Data Engineering & Pipelines (10%): Design and optimize data workflows and real-time processing pipelines using technologies like Airflow, Spark, Kafka, SQL, and NoSQL databases such as DynamoDB, PostgreSQL, or Redis.
- DevOps & Automation (10%): Build CI/CD pipelines and manage infrastructure-as-code with tools like Docker, Kubernetes, Terraform, Jenkins, and GitHub Actions.
- Collaboration & Strategy (10%): Collaborate with founders, AI researchers, and the product team to align on strategic decisions and technical roadmaps.
- 5 years of full-stack development experience with a focus on AI-driven or data-centric applications.
- Proven experience in building customer-facing applications, both frontend (React, Vue, etc.) and backend (Node.js, Python, Go, etc.).
- Strong understanding of AI/ML technologies, including NLP and experience with LLMs (such as GPT and BERT).
- Experience in designing and optimizing data pipelines with technologies like Airflow, Spark, Kafka, and related tools.
- Expertise in cloud computing platforms (AWS, GCP, Azure) and container orchestration using Kubernetes and Docker.
- Proficiency in DevOps practices—building CI/CD pipelines, automating deployments, and managing infrastructure-as-code using Terraform.
- Experience in early-stage startups, with a hands-on approach and the ability to manage various roles and tasks.
- Familiarity with vector databases (Pinecone, FAISS, Weaviate) for NLP applications.
- Knowledge of MLOps tools and frameworks like MLflow or SageMaker.
- Contributions to open-source AI/ML projects would be a plus.
- Equity Eligible
- Health Benefits: Medical, dental, and vision insurance.
- Unlimited Vacation Time
Posted By: Avery Burrell