AI Native Software Engineer

Description

The company builds the next generation of engineers who use AI as a core part of their daily work, not as an extra tool. The role is a full-stack engineering position where you design, build, and ship production software with AI tooling as standard practice.

You will build production software for client programs across many industries. That software connects to and supports agentic AI systems, so you will learn how your full-stack code fits with agent architecture, LLM APIs, and enterprise AI pipelines. This is a core engineering role in a high-demand market, with a route into the Forward Deployed Engineer program for engineers who build agentic depth.

The company works across every industry, many enterprise technology stacks, and organizations of all sizes. It has about 791,000 people serving clients in more than 120 countries and works closely with major technology partners.

Responsibilities

• Use AI coding assistants every day in delivery, often and with clear gains in productivity and output quality
• Call LLM APIs from live production code, manage token limits and latency, and build early abstraction layers
• Use AI across the software delivery cycle for tests, debugging, code review, and prompt design for development tasks
• Judge when AI output is reliable enough for production and when it is not, and take ownership of its quality in your scope
• Define and track KPIs that show whether AI-assisted workflows pay off, and report productivity and quality results to project stakeholders
• Own work from design to production support within Agile sprints, alongside client engineering teams
• Build application layers, APIs, and interfaces that link full-stack systems to agentic backends, including data flows, context handoffs, and integration points with AI pipelines
• Contribute reusable components, shared knowledge, and internal AI tooling standards for the wider team

Requirements

• Proficiency in at least one backend language: Python, Java, or TypeScript
• Commercial production software experience, or equivalent work shown through academic projects, internships, or personal projects you have shipped
• Hands-on use of AI tools in daily engineering, with examples of solving real problems, refining outputs, and improving delivery
• Direct experience calling LLM APIs in production code, with an understanding of token management, latency, and cost trade-offs
• Ability to validate and improve AI-generated output, and an understanding of its limits and responsible use
• Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field
• Working knowledge of JavaScript, HTML, and CSS
• Familiarity with cloud basics on AWS, Azure, or GCP, plus Docker containers and CI/CD pipelines
• Understanding of Agile delivery fundamentals
• Experience with SQL or NoSQL databases
• Preferred: production experience with agentic system concepts, such as orchestration frameworks (LangChain, LangGraph, or similar) and RAG pipelines, and how full-stack apps connect to agent-based architecture. Conceptual understanding is required.

Conditions

Hiring decisions are made without regard to age, race, creed, colour, religion, sex, nationality, ancestry, disability, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship, or any other characteristic protected by applicable law.

Benefits

• Access to vendor fellowship programs within the engineering teams of Anthropic, OpenAI, Microsoft, and Google
• Structured AI certification pathways
• A defined development track toward agentic and forward-deployed engineering