Senior AI Software Engineer (Full Stack)

ASAL AI/R&D group is seeking Senior AI Software Engineers who thrive at the intersection of software engineering and applied AI. In this role, you'll be responsible for designing, constructing, and managing robust AI-centric solutions where technologies like Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents form the foundation of the system rather than being added features. You will contribute end-to-end across the stack of both product and project initiatives, from user interfaces and backend services to data pipelines and AI reasoning layers. This is a hands-on role for engineers who want to build reliable AI systems that operate at scale.

Key Responsibilities

• Design and implement AI-first application features driven by LLMs, retrieval pipelines, and AI reasoning workflows
• Build, optimize, and maintain RAG pipelines, including chunking strategies, indexing, retrieval quality, grounding, citation mechanisms, and evaluation
• Develop and govern prompt factories: prompt templating, versioning, testing, and reuse across solutions
• Contribute across the full application stack front-end integration, backend APIs and services, and data ingestion and processing layers
• Design AI systems with production constraints in mind: latency, cost, reliability, observability, and safe fallback behavior
• Apply Agile/Scrum/Kanban methodologies to deliver incremental, testable, maintainable software
• Use AI-assisted development tools responsibly, validating all outputs through testing and peer review
• Write clean, maintainable, well-tested code; lead and participate in code reviews
• Produce and maintain technical documentation: design notes, architecture diagrams, runbooks
• Mentor junior and Train-to-Hire (TTH) engineers through structured technical guidance and code reviews
• Uphold ASAL AI/R&D standards for security, privacy, and information protection

Desired Candidate Profile

BSc in Computer Science, Software Engineering, AI, or a related discipline. 4+ years of professional software engineering experience delivering production systems. 2+ years of hands-on experience building AI-centric systems (LLM-based, RAG, agentic AI, or ML-driven applications). Demonstrated experience delivering and operating LLM-based solutions in production (LLMOps). Ability to contribute meaningfully across multiple layers of an application stack. Strong written and verbal English communication skills. Strong collaboration, analytical, and organizational skills. Extra Credit Experience with multimodal GenAI: text, image, document understanding, or multimodal RAG.