Senior Software Engineer – Agentic AI

About the Role

We are seeking a highly capable Senior Software Engineer – Agentic AI to join our Engineering team in Kuala Lumpur on a full-time basis. This role is responsible for designing, building, and advancing intelligent software systems that leverage large language models, retrieval-augmented generation, and agentic workflows to address complex business needs at production scale. The successful candidate will combine strong backend engineering expertise with practical experience in machine learning and modern AI application architecture, while maintaining the standards of reliability, security, and maintainability expected in an established corporate environment.

You will work closely with engineers, product stakeholders, and cross-functional partners to deliver robust AI-enabled services, APIs, and platform capabilities. The position requires sound judgment in system design, disciplined software engineering practices, and the ability to translate emerging AI patterns into dependable enterprise solutions. In addition to hands-on development, you will contribute technical guidance, mentor colleagues, and help shape engineering standards for the responsible use of AI across distributed systems and cloud-based environments.

Key Responsibilities

1. Design and develop production-grade agentic AI applications using Python and modern software engineering practices.
2. Architect and implement LLM-powered services, including prompt workflows, tool use, orchestration layers, and retrieval-augmented generation pipelines.
3. Build secure, scalable, and maintainable backend systems, APIs, and microservices that integrate AI capabilities into broader platforms.
4. Collaborate with product, engineering, and business stakeholders to translate requirements into well-structured technical solutions.
5. Establish robust evaluation frameworks for model quality, relevance, latency, cost efficiency, and operational performance.
6. Integrate vector databases, knowledge retrieval components, and workflow automation tools to support intelligent task execution.
7. Apply testing, debugging, and observability practices to ensure reliability, traceability, and high service availability in production.
8. Optimize system performance across distributed environments, including cloud infrastructure, containers, and CI/CD pipelines.
9. Embed security, privacy, and responsible AI considerations into system design, data handling, and deployment processes.
10. Support MLOps processes for versioning, experimentation, deployment, monitoring, and continuous improvement of AI services.
11. Provide technical leadership through architecture reviews, code reviews, documentation, and mentoring of engineers.
12. Contribute to engineering standards, reusable frameworks, and best practices for AI-enabled software development.

Required Qualifications

1. Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline, or equivalent practical experience.
2. Demonstrated experience in software engineering with strong proficiency in Python and backend application development.
3. Hands-on experience building applications with large language models, AI agents, prompt engineering, and retrieval-augmented generation.
4. Strong understanding of machine learning, deep learning, and natural language processing concepts relevant to real-world product delivery.
5. Experience with LLM orchestration frameworks, API design and integration, and service-oriented or microservices-based architectures.
6. Solid foundation in system design, distributed systems, data structures, algorithms, and performance optimization.
7. Practical experience with cloud platforms, containerization, version control using Git, and automated CI/CD workflows.
8. Familiarity with vector databases, model evaluation techniques, and MLOps practices for deployment and lifecycle management.
9. Proven ability to write clean, testable, and maintainable code with disciplined debugging and quality assurance practices.
10. Understanding of security, privacy, and governance considerations for AI systems operating with sensitive or business-critical information.
11. Strong communication skills with the ability to explain technical decisions clearly to both engineering and non-technical stakeholders.
12. Demonstrated capability to mentor peers, influence technical direction, and operate effectively in collaborative delivery teams.

Nice to Have

1. Experience deploying multi-agent systems or autonomous workflows in production environments with measurable operational outcomes.
2. Exposure to enterprise integration patterns, event-driven architectures, and complex service interoperability challenges.
3. Knowledge of advanced model tuning, experimentation frameworks, or techniques for improving groundedness and response quality.
4. Experience designing governance controls, auditability mechanisms, and safeguards for responsible AI adoption at scale.
5. Familiarity with cost management strategies for LLM usage, infrastructure efficiency, and resource optimization in cloud environments.
6. Prior involvement in establishing technical standards, reusable internal platforms, or shared engineering enablement capabilities.

What We Offer

1. The opportunity to work on strategically important AI initiatives with meaningful technical scope and visible organizational impact.
2. A collaborative engineering environment that values disciplined execution, high standards, and thoughtful innovation.
3. Exposure to modern AI architectures, scalable cloud platforms, and complex distributed systems in a production setting.
4. Opportunities for technical leadership, mentoring, and continued professional growth within a strong engineering function.
5. A full-time role based in Kuala Lumpur with the chance to contribute to long-term platform and product development.
6. A professional workplace that emphasizes quality, accountability, security, and sustainable software engineering practices.