Agentic AI Software Engineer

Overview We are seeking a senior software engineer with a strong full-stack background who has evolved into AI engineering and agent development. This role focuses on building, deploying, and optimising intelligent agents and AI-driven workflows that interact with enterprise systems, data sources, and users. The successful candidate will have hands-on experience developing production-grade AI applications using large language models (LLMs), retrieval-augmented generation (RAG), agent orchestration frameworks, and modern software engineering practices. This position is centred on designing and building AI agents rather than purely traditional application development., AI Agent Development

• Design and develop AI agents capable of reasoning across complex business processes and interacting with tools, APIs, and enterprise systems.
• Build intelligent support and workflow automation agents that understand intent, retrieve information, and execute tasks.
• Develop agentic workflows combining LLMs, structured data, business logic, external services, and retrieval mechanisms.
• Create memory, context, and personalisation capabilities to improve agent effectiveness.
• Implement guardrails, monitoring, evaluation frameworks, escalation paths, and human oversight mechanisms.
• Measure and improve agent performance across quality, reliability, latency, utilisation, and cost metrics.

Full-Stack Application Development

• Build user-facing applications that enable interaction with AI-powered experiences.
• Develop modern frontend applications using frameworks such as React, Angular, Next.js, or comparable technologies.
• Create backend services, APIs, orchestration layers, and integration services using Python-based frameworks.
• Translate advanced AI capabilities into practical business applications and intuitive user experiences.
• Own solutions end-to-end from architecture through deployment and support.

Data & AI Infrastructure

• Build and maintain data ingestion, integration, and transformation pipelines.
• Develop and support retrieval-augmented generation (RAG) solutions and enterprise search capabilities.
• Design systems supporting context management, retrieval, memory, and personalisation.
• Integrate AI solutions with databases, APIs, analytics platforms, and enterprise applications.
• Ensure data quality, security, reliability, and scalability across AI systems.

LLM Engineering

• Integrate and orchestrate large language models within production environments.
• Design prompting strategies, retrieval approaches, tool-calling frameworks, and multi-step workflows.
• Build AI-powered capabilities including conversational assistants, document intelligence, semantic search, and workflow automation.
• Evaluate models, architectures, and AI platforms for performance, reliability, business fit, and cost efficiency.
• Establish monitoring and evaluation methodologies for production AI solutions.

Engineering Excellence

• Leverage AI-assisted development tools to improve engineering productivity while maintaining high code quality standards.
• Stay current with emerging AI frameworks, tooling, and industry best practices.
• Implement CI/CD, testing, observability, security, and production monitoring practices.
• Support reliable deployment and ongoing optimisation of AI-enabled applications.

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
• 8+ years of professional software engineering experience.
• Strong full-stack development experience across frontend and backend technologies.
• Proven experience building and maintaining RESTful APIs and backend services.
• Experience working with data-intensive applications and enterprise integrations.
• Hands-on experience developing AI agents, autonomous workflows, or LLM-powered applications.
• Strong understanding of LLMs, RAG, tool usage, orchestration frameworks, and AI application architectures.
• Experience integrating AI systems with APIs, databases, enterprise platforms, and third-party services.
• Frontend experience with React, Angular, Next.js, or similar frameworks.
• Experience using AI-assisted development tools within software delivery workflows.
• Experience designing agent memory, retrieval, context, evaluation, or reasoning systems.
• Strong understanding of cloud-native application development and deployment.

Preferred Qualifications

• Experience with modern data-platform or lakehouse architectures.
• Experience deploying applications on public cloud platforms.
• Experience with CI/CD pipelines, infrastructure automation, and cloud operations.
• Experience working within agile software delivery environments.
• Experience building highly scalable enterprise applications.

What Success Looks Like

• Demonstrates an AI-first engineering mindset focused on intelligent workflows rather than simple AI integrations.
• Comfortable operating across software engineering, AI, data, and infrastructure domains.
• Balances innovation with reliability, observability, governance, and security.
• Strong product mindset with a focus on measurable business outcomes.
• Effective communicator who collaborates with technical and non-technical stakeholders.
• Thrives in fast-moving environments where requirements and technologies evolve rapidly.