AI-Native Full-Stack Engineer

Position Overview We are seeking a Senior AI-Native Full-Stack Engineer to join Upstart AEC. This role sits at the intersection of large language model (LLM) systems, agentic workflows, and scalable backend architecture. You will design and build production-grade AI applications from the ground up, translating complex business requirements into intelligent, automated systems. The role is backend-first, with a strong focus on AI architecture, integration, and implementation. Frontend exposure is helpful but not the primary focus. You should be comfortable working in cloud environments (on-premise and cloud-based platforms), with strong cloud-agnostic competency. Deep expertise in a specific cloud provider is not required, but a solid understanding of cloud architecture principles is essential.

Key Responsibilities

AI Systems & Architecture Design and build AI-native applications leveraging LLMs and agentic frameworks Architect and implement Retrieval-Augmented Generation (RAG) pipelines and vector store integrations Implement autonomous, goal-driven AI workflows using LangChain and related frameworks Ensure performance, observability, and reliability of AI-powered systems Build core AI architecture, integrations, and implementations from scratch or using AI automation platforms for smaller engagements

Application & Backend Development Develop and scale RESTful APIs and microservices architectures Build modern AI applications using Python (primary) and TypeScript Integrate backend systems using Python or Go Design and manage data systems using Postgres and Redis Contribute to CI/CD pipelines and maintain strong development best practices Collaborate with product and business stakeholders to translate logistics, monetization, and operational requirements into scalable technical systems

Required Skills

Programming & Backend Expertise Strong proficiency in Python for backend development and AI model integration Strong proficiency in JavaScript/TypeScript Extensive experience designing, scaling, and maintaining RESTful APIs and microservices Deep understanding of Postgres and Redis Experience building production-grade systems

AI-Native & Agentic Development Hands-on experience with LangChain or similar LLM orchestration frameworks Strong understanding of agentic AI principles and autonomous system design Experience working with LLMs and generative AI tooling Practical experience with: RAG architectures Vector databases and embeddings Semantic search Dynamic reasoning and task planning workflows

Cloud & Systems Strong understanding of cloud architecture principles Comfortable working across cloud and on-premise environments Cloud-agnostic competency (AWS experience is beneficial but not mandatory)

Observability & Tooling (Preferred) Experience with AI observability platforms such as LangSmith or similar tools Familiarity with monitoring, debugging, and optimizing LLM application performance

General & Soft Skills Strong experience with Git, CI/CD pipelines, and agile development practices Excellent written and verbal communication skills Exceptional problem-solving ability High ownership mindset — able to independently drive initiatives from concept to deployment Comfortable operating in ambiguous, fast-paced environments Strong product intuition and ability to connect technical decisions to measurable business outcomes

What Success Looks Like You independently design and ship scalable, production-ready AI systems You proactively identify architectural improvements and performance optimizations You translate business challenges into intelligent, automated workflows You contribute to building a strong AI-native engineering culture