At a Glance
- Tasks: Lead the development of AI-native applications and design intuitive user interfaces.
- Company: Join a cutting-edge tech company at the forefront of AI innovation.
- Benefits: Enjoy competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and continuous learning.
- Why this job: Make a real impact by building systems that empower AI to solve complex problems.
- Qualifications: 5-8 years in full-stack engineering with expertise in React, TypeScript, and backend systems.
The predicted salary is between 80000 - 100000 £ per year.
Requirements
- Experience: Typically 5–8 years of professional full-stack software engineering experience.
- Frontend Stack: Deep expertise in React, TypeScript, and modern CSS/HTML. Ability to build complex, data-rich applications.
- Backend Stack: Proven experience with RDBs (e.g. PostgreSQL) and Object Stores (e.g. s3).
- API Design: Strong experience designing and consuming RESTful and/or GraphQL APIs with a focus on reliability and security.
- AI Development Tooling: Expert-level proficiency with modern agentic development environments (e.g., Cursor, Claude Code, Windsurf) to accelerate the shipping cycle.
- Architecture: Solid understanding of distributed systems, serverless architectures, and relational database modeling.
- Deployment: Familiarity with CI/CD practices and tools (e.g. Jenkins) and cloud providers for compute/network (e.g. AWS ALBs/ECS).
- Communication: Ability to bridge the gap between technical LLM capabilities and practical, user-facing product features.
- Agentic Frameworks: Hands-on experience with agentic orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, or PydanticAI).
- (Desirable) AI UX Patterns: Deep understanding of 'Agentic UX' patterns, such as ReAct, streaming UI updates, generative UI, and proactive notifications.
- (Desirable) LLM Observability: Experience with monitoring and evaluation tools for AI agents (e.g., LangSmith, Braintrust, or Helicone) to track agent reliability and cost.
- (Desirable) Tool-Calling Expertise: Proven track record of building 'Tools/Functions' for LLMs to interact with third-party SaaS platforms or internal databases.
- (Desirable) Durable Runtimes: Hands-on experience with durable runtime frameworks such as temporal or similar.
- (Desirable) Storage: Experience with Supabase e.g. Row Level Security (RLS), and database migrations.
- (Desirable) Vector Databases: Familiarity with pgvector or other vector stores for RAG (Retrieval-Augmented Generation) workflows.
- (Desirable) Real-time Systems: Experience with WebSockets or Supabase Realtime to provide instant feedback for long-running agentic tasks.
What the job involves
- As a Senior Full-Stack Engineer (3D), you will be a lead contributor in building the next generation of AI-native applications.
- You sit at the intersection of robust backend orchestration and intuitive frontend design.
- Your primary mission is to design and implement 'agentic' workflows/harnesses/systems where AI doesn't just respond to prompts but proactively executes tasks, manages state, and interacts with external tools to solve complex user problems.
- You will work across the entire stack, leveraging best in class frameworks and tooling for both frontend, data storage, runtime and API design.
- You will work closely with the UX Research team to understand and develop new interfaces and interaction techniques.
- End-to-End Engineering: Lead the development of full-stack features, from database schema design to high-fidelity UI implementation.
- Agentic Workflow Orchestration: Design and implement backend logic that allows AI agents to interact with APIs, databases, and long-running processes autonomously.
- Agentic UX Design: Build 'Human-in-the-loop' interfaces that allow users to monitor, steer, and collaborate with AI agents in real-time.
- Infrastructure & Security: Architect secure and performant backend systems using best practices and design patterns, to support high-concurrency AI operations.
- State Management: Manage complex, asynchronous application states where data may be updated concurrently by both users and background AI agents.
- Performance Optimization: Build efficient applications and services, understand how to best to maximize both perceived and actual user experience. Optimize the entire request-response lifecycle, focusing on minimizing latency in LLM streaming and database queries.
- Technical Health: Maintain high standards for code quality, focusing on static type safety, clean architectural consistency and comprehensive unit and integration testing.
Lead Full-Stack Engineer, AI-Agentic Platforms employer: Autodesk
As a Lead Full-Stack Engineer at our innovative AI-Agentic Platforms, you will thrive in a dynamic work culture that prioritises collaboration and creativity. We offer competitive benefits, including professional development opportunities and a commitment to employee growth, all within a vibrant location that fosters cutting-edge technology and forward-thinking solutions. Join us to be part of a team that is shaping the future of AI applications while enjoying a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Full-Stack Engineer, AI-Agentic Platforms
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. You never know when a casual chat might lead to your next big opportunity.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your best projects, especially those that align with AI-native applications. Make sure to include links to your GitHub or any live demos. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for the interview like it’s the Super Bowl! Research the company, understand their products, and be ready to discuss how your experience with React, TypeScript, and backend systems can help them achieve their goals. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search. Let’s get you on board!
We think you need these skills to ace Lead Full-Stack Engineer, AI-Agentic Platforms
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with React, TypeScript, and all those backend goodies like PostgreSQL. We want to see how you’ve built complex applications, so don’t hold back on the details!
Tailor Your Application:Take a moment to customise your application for this role. Mention specific projects where you've designed RESTful or GraphQL APIs, and how you’ve tackled challenges in AI development tooling. It’ll make your application stand out!
Be Clear and Concise:When writing your application, keep it clear and to the point. We love a good story, but we also appreciate brevity. Make sure your key achievements shine through without unnecessary fluff.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to get your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Autodesk
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in React, TypeScript, and modern CSS/HTML. Be ready to discuss your experience building complex applications and how you’ve tackled challenges in the past. Brush up on your backend knowledge too, especially with PostgreSQL and API design.
✨Showcase Your AI Development Skills
Familiarise yourself with the latest agentic development tools like Cursor and Claude Code. Be prepared to share specific examples of how you've used these tools to enhance your workflow or improve project outcomes. Highlight any experience with agentic orchestration frameworks as well.
✨Communicate Clearly About Architecture
You’ll need to bridge the gap between technical capabilities and user-facing features. Practice explaining complex concepts in simple terms, especially around distributed systems and serverless architectures. This will show your ability to collaborate with non-technical team members.
✨Prepare for Real-World Problem Solving
Expect scenario-based questions where you’ll need to demonstrate your problem-solving skills. Think about how you would design a system that allows AI agents to interact autonomously with APIs and databases. Be ready to discuss your approach to performance optimisation and state management.
