AI Software Engineer

Responsibilities:

1. AI Agent Development

• Design, build, and deploy production-ready AI agents that automate complex enterprise workflows.

• Develop intelligent systems for quoting, pricing, product recommendations, and cross-selling.

• Integrate large language models from providers such as OpenAI, Anthropic, and Google Gemini into real-world applications.

• Build reliable agentic workflows that can reason through multi-step tasks, interact with external systems, and produce useful business outcomes.

• Evaluate and improve agent performance, reliability, and usability in production environments.

2. Full-Stack Product Engineering

• Build and ship end-to-end product features using TypeScript, React, and Next.js.

• Develop responsive frontend interfaces and scalable backend services.

• Own features from initial design and implementation through testing, deployment, and iteration.

• Make sound technical decisions while balancing product quality, development speed, and maintainability.

• Collaborate with the team to identify customer problems and translate them into practical software solutions.

3. Enterprise Systems Integration

• Integrate AI-powered applications with enterprise resource planning systems, including SAP.

• Build workflows that connect AI agents with existing enterprise data, business rules, and operational processes.

• Handle complex integrations involving product configurations, inventory, pricing, freight, tariffs, and customer information.

• Ensure AI-powered features operate reliably within established enterprise software environments.

4. Enterprise Deployment & Data Infrastructure

• Support secure, GDPR-compliant deployments for European enterprise customers.

• Contribute to data residency, infrastructure, and deployment requirements for international customers.

• Build systems that meet enterprise expectations for reliability, security, and operational performance.

• Help resolve technical challenges associated with deploying AI applications in complex customer environments.

5. Product Ownership & Iteration

• Take ownership of product features from concept through production release.

• Work closely with the founders and other team members to understand customer requirements and prioritise product improvements.

• Translate customer feedback into actionable technical solutions.

• Iterate quickly, test new ideas, and improve product capabilities based on real-world usage.

• Contribute to technical architecture and engineering decisions as the company scales.

6. AI Innovation & Engineering Excellence

• Stay current with emerging AI models, agentic frameworks, coding assistants, and software engineering techniques.

• Experiment with AI-native development workflows to accelerate implementation and improve productivity.

• Evaluate new tools and approaches beyond those currently used in the role.

• Contribute to a culture of technical curiosity, rapid learning, and high-quality execution.

Requirements:

1. Full-Stack Product Engineering

• Approximately 2–4 years of full-stack product engineering experience, ideally within a startup environment.

• Strong proficiency in TypeScript and React.

• Demonstrated experience building and shipping full-stack products or production features.

• Ability to work across frontend and backend systems rather than specialising exclusively in one layer.

• Strong software engineering fundamentals, problem-solving ability, and attention to product quality.

2. Hands-On AI Systems Development

• Direct experience building or deeply integrating AI systems and agentic products.

• Experience must extend beyond using ChatGPT or Claude with custom prompts, skills, or basic wrappers.

• Demonstrated ability to integrate AI models into functional applications and production workflows.

• Experience designing, implementing, or maintaining multi-step AI-powered processes.

3. Agentic Framework Experience

• Hands-on experience building projects using an agentic framework or harness, such as:

LangGraph

Mastra

OpenAI Agents SDK

Comparable agent orchestration frameworks

• Understanding of how to structure agent workflows, integrate tools, manage execution, and handle multi-step tasks.

4. Genuine AI Curiosity

• Demonstrates genuine interest in AI engineering and actively follows new tools, techniques, and developments beyond immediate job requirements.

• Willingness to experiment with emerging models and frameworks and apply them to practical engineering problems.

• Strong learning agility and the ability to operate effectively in a rapidly evolving technical environment.