{"id":3609336,"url":"https://alion.io/job/asus-engineering-manager-ai-engineering-llm-systems","title":"Engineering Manager – AI Engineering & LLM Systems","company":{"id":13383,"name":"Asus","domain":"asus.com","url":"https://alion.io/company/asus","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"D","score":40,"open_postings":12,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-06T05:58:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":10000,"max":18000,"currency":"SGD","period":"month","gross":true,"usd_annual":169080},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"PyTorch","optional":false}],"status":"live","first_seen_at":"2026-11-02T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-11-02T00:00:00Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"AICS builds Healthcare AI solutions that improve clinical workflows through large language models, agentic AI, and modern AI engineering.\nWe are looking for an Engineering Manager to lead a team of Machine Learning Engineers building production-ready LLM applications, AI infrastructure, and clinical AI systems.\n\nKey Responsibilities\nLead and grow a high-performing Machine Learning Engineering team.\nDrive the design, development, and deployment of production LLM applications and AI systems.\nBuild scalable AI engineering workflows covering model evaluation, experimentation, deployment, and continuous improvement.\nLead the development of agentic AI capabilities, including multi-agent workflows, tool integration, memory, and orchestration.\nEstablish engineering best practices for AI development, software quality, testing, and MLOps.\nWork closely with AI Research, Product, and Software Engineering teams to translate research into production products.\nContinuously evaluate emerging AI technologies and adopt new techniques that improve product quality and engineering productivity.\n\nRequirements:\n8+ years of software engineering, machine learning engineering, or AI engineering experience.\n3+ years leading technical engineering teams.\nProven experience delivering AI products into production.\nTechnical Expertise\nCandidates should have practical, hands-on experience with most of the following:\nLarge Language Models (LLMs) and Generative AI application development\nModel fine-tuning or adaptation for domain-specific use cases\nLLM evaluation and benchmarking\nRAG and knowledge retrieval systems\nAgentic AI frameworks and workflow orchestration\nPrompt engineering and structured tool calling\nPyTorch and Hugging Face ecosystem\nAI deployment, inference optimization, and MLOps\nCloud-native engineering (Docker, Kubernetes, Azure or GCP)\nSkills\nAi, Generative AI Application Development and Deployment, AI Agents, Technology Expertise, Extensive Work Experience, Experimentation, Cloud Native Architecture, leading technical teams, Software Engineering, Domain Adaptation Techniques, AI Evaluation, MLOps, Hugging Face, PyTorch, LLMs, AI Safety, Hands-On Experience, Product Development, 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