Job Description – AI Native Developer

Team: AI Foundry – Central AI Engineering Team Function: Technology / Engineering Role: AI Native Developer / AI Engineer Experience: Min 3 Years - Max 8 Years

About the Role

We are looking for passionate, curious, and technically strong AI Native Developers to join our AI Foundry , a specialized central engineering team focused on accelerating AI-driven innovation and software development across the organization. The AI Foundry operates as a central pool of AI engineering specialists , bringing together developers who use artificial intelligence not merely as a coding assistant but as a fundamental part of how software is designed, developed, tested, and delivered. As an AI Native Developer, you will work on a variety of strategic internal initiatives, special projects, intelligent automation solutions, and AI-powered applications . You will be assigned to different projects based on business priorities, contributing as an AI engineering expert while remaining part of the central AI Foundry team. Unlike traditional software development roles, this position emphasizes agent-driven development, specification-driven engineering, AI-assisted problem-solving, and rapid experimentation to build reliable, scalable, production-ready solutions. We are looking for developers who can combine strong programming fundamentals with emerging AI engineering capabilities to fundamentally rethink how software is built.

Key Responsibilities

1. AI-Native Software Development

• Design, develop, and deliver software applications using AI-powered coding agents such as Claude Code, Cursor, GitHub Copilot, and similar tools.
• Adopt an AI-first development approach , leveraging coding agents throughout the software development lifecycle, from planning and implementation to testing and deployment.
• Build functional prototypes, internal applications, and production-ready solutions with speed, efficiency, and engineering discipline.
• Maintain strong ownership of code quality, architecture, security, reliability, and maintainability, regardless of whether code is written manually or generated through AI.

2. Strategic Internal Projects & Innovation

• Contribute to special projects and strategic technology initiatives driven by the AI Foundry.
• Develop innovative internal tools, workflow automation solutions, AI-powered applications, and intelligent business systems that improve organizational productivity and operational efficiency.
• Collaborate with different business and technology functions to understand challenges, identify opportunities, and translate requirements into practical engineering solutions.
• Work across multiple project domains, adapting quickly to evolving business priorities and technology requirements.

3. Agentic Engineering & Workflow Automation

• Design and implement agentic workflows capable of executing complex, multi-step development and business processes.
• Integrate LLMs with APIs, enterprise systems, databases, and external tools to build intelligent applications.
• Develop workflows involving tool calling, task orchestration, parallel execution, contextual reasoning, and human-in-the-loop validation.
• Explore and implement AI agents that can independently perform defined tasks while operating within appropriate guardrails and approval mechanisms.

4. Specification-Driven Development

• Translate business requirements, user stories, and functional expectations into structured technical specifications.
• Define clear acceptance criteria, expected outputs, test cases, and constraints that AI coding agents can execute against.
• Use specifications to guide development, reduce ambiguity, and improve the consistency of AI-generated software.
• Collaborate with stakeholders to ensure the delivered solutions meet business and user expectations.

5. AI Quality, Testing & Reliability

• Review, test, debug, and validate AI-generated code and application outputs.
• Implement automated testing, code reviews, runtime checks, and validation frameworks.
• Identify and mitigate issues such as hallucinations, insecure code, incorrect outputs, performance bottlenecks, and unreliable agent behaviour.
• Ensure that AI-powered solutions meet appropriate standards for accuracy, security, performance, and operational reliability.

6. Continuous Innovation & Knowledge Sharing

• Experiment with emerging AI development tools, frameworks, models, and engineering practices.
• Evaluate new technologies and identify opportunities to improve development speed, quality, and cost efficiency.
• Contribute to reusable components, shared tools, engineering standards, and best practices within the AI Foundry.
• Share learnings, demonstrate prototypes, and collaborate with fellow AI Native Developers to strengthen the organization's AI engineering capabilities.

Required Technical Competencies – Mandatory

1. Agent-Driven Development Ability to develop software primarily through AI coding agents such as Claude Code, Cursor, and GitHub Copilot, including effective management of context, development tools, workflows, and guardrails to ensure reliable outputs.
2. Specification-Driven Development Ability to translate business requirements and user stories into structured technical specifications, clear acceptance criteria, and executable development instructions for AI agents.
3. LLM & Prompt Engineering Working understanding of large language models, LLM APIs, prompt engineering, context management, and model limitations, including hallucinations, context windows, latency, and cost considerations.
4. Agentic Workflows Understanding of multi-step AI agent workflows, tool calling, task orchestration, parallel execution, and human-in-the-loop checkpoints. Ability to design, implement, and troubleshoot agent-based solutions.
5. AI Output Verification Ability to critically evaluate, test, debug, and validate AI-generated code and outputs using automated tests, code reviews, runtime checks, and structured verification techniques.
6. Core Programming & Software Engineering Fundamentals

• Strong foundational knowledge of at least one programming language, preferably Python, TypeScript, JavaScript, Java, or C++.
• Understanding of object-oriented programming, data structures, algorithms, APIs, databases, and software design principles.
• Ability to understand, review, debug, and maintain code generated by AI coding tools.
• Familiarity with Git, version control, and collaborative software development practices.

Additional Technical Competencies – Good to Have

1. AI Application Development Experience building AI-powered applications or features such as conversational interfaces, intelligent search, document processing, workflow automation, or AI-enabled business tools, ideally deployed for real users.
2. RAG & Vector Search Understanding or hands-on experience with Retrieval-Augmented Generation (RAG), embeddings, semantic search, and vector databases. Experience retrieving information from enterprise documents, HR policies, process documentation, and structured business records is an advantage. Knowledge of pgvector with PostgreSQL is preferred; Pinecone or Chroma experience is also valuable.
3. AI Frameworks & Protocols Familiarity with AI development frameworks and orchestration tools, including LangChain.js, LangGraph.js, LlamaIndex, and Model Context Protocol (MCP). Experience connecting AI agents with enterprise platforms such as Jira, SharePoint, HCM applications, and other internal business systems is desirable.
4. Deployment & Operations Experience or exposure to Docker, CI/CD pipelines, cloud environments, API deployment, application monitoring, and tracking AI model quality, latency, and operating costs.

Desired Behavioural Competencies

AI-First Mindset: Naturally approaches software development by exploring how AI agents, automation, and intelligent tools can improve the way solutions are engineered. Problem-Solving & Critical Thinking: Demonstrates strong analytical thinking, challenges assumptions, and can independently break down complex business problems into practical technical solutions. Curiosity & Learning Agility: Actively experiments with emerging AI technologies and adapts quickly to new tools, frameworks, and development practices. Ownership & Accountability: Takes responsibility for delivering working, reliable solutions rather than merely generating code or completing assigned development tasks. Adaptability & Collaboration: Comfortable working on diverse projects, engaging with different stakeholders, and operating in a dynamic, cross-functional environment. Innovation & Initiative: Proactively identifies opportunities to simplify processes, eliminate repetitive work, and build smarter applications using AI.

Education & Experience

• Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, Artificial Intelligence, or a related discipline.
• Experience: 0–5 years. Fresh graduates with demonstrated AI-native development capabilities, strong technical fundamentals, and relevant hands-on projects are encouraged to apply.
• Practical experience with AI coding agents, personal projects, internships, hackathons, open-source contributions, or deployed AI applications will be considered valuable.
• Demonstrated ability to build working solutions and explain their technical decisions will be valued alongside formal qualifications.

What Makes This Role Different?

This is not a conventional software development position where AI is used occasionally to assist with coding. At the AI Foundry, AI is central to the engineering process . You will have the opportunity to:

• Work within a specialized, centrally managed team of AI engineering specialists.
• Contribute to diverse, high-impact internal projects instead of being restricted to a single product or application.
• Build and deploy solutions using AI coding agents and modern AI engineering techniques.
• Experiment with emerging AI technologies and convert promising ideas into practical business applications.
• Collaborate with business and technology stakeholders to solve real organizational challenges.
• Help establish new standards for how software is designed, developed, and delivered in an AI-native engineering environment.