{"id":3262698,"url":"https://alion.io/job/m1-assistant-general-manager-ai-engineering","title":"Assistant General Manager, AI Engineering","company":{"id":49914,"name":"M1","domain":"m1.com.sg","url":"https://alion.io/company/m1-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","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":14000,"currency":"SGD","period":"month","gross":true,"usd_annual":131460},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-26T00:00:00Z","board_verified":false,"closed_at":null,"days_open":8,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":8},"description":"Role Summary\nWe are looking for an Assistant General Manager, AI Engineering to lead the forward-deployed AI engineering function, partnering directly with business teams to identify, build and scale production-grade AI solutions that deliver measurable business outcomes.\nReporting to the Head of Data & AI, the role is accountable for end-to-end delivery, engineering standards, technical architecture, production reliability, and the development of a high-performing AI engineering team.\nJob Responsibilities:\n\nForward deployed delivery\nPartner with business stakeholders to understand workflows, test assumptions and define measurable outcomes.\nLead solutions from discovery and prototype to production, user adoption and support; turn reusable components into shared capabilities.\nAI applications and integration\nLead the development of services, APIs and user-facing workflows using LLMs, retrieval and tool execution.\nIntegrate enterprise applications through authenticated APIs and MCP where appropriate, selecting deterministic workflows, agents or conventional ML based on the problem.\nContext engineering\nDesign retrieval, chunking, embeddings, reranking and context assembly.\nManage instructions, tool definitions, conversation state, memory, freshness and token budgets; preserve source provenance and enforce access permissions.\nAgent harness engineering\nBuild the runtime around models: tool contracts, orchestration, state persistence, checkpoints, bounded execution, retries, timeouts and recovery.\nPrevent duplicate side effects and enforce approval boundaries for consequential actions.\nEvaluation and production operations\nEstablish representative evaluation datasets and regression gates for model, prompt, retrieval and tool changes.\nTrace failures and monitor task success, groundedness, latency and cost per completed task.\nLead release readiness, rollback and incident diagnosis with platform teams.\nData and model foundations\nBuild reliable ingestion and transformation pipelines with Data Engineering.\nMaintain data quality, schemas and lineage.\nApply deep learning or conventional ML where appropriate, with robust validation and monitoring.\nTechnical leadership and controls\nSet architecture and code quality standards; prioritise delivery with business owners.\nWork with Cyber Security to implement identity, least privilege, secrets management, auditability and prompt-injection defences.\nEnsure coding agents are used with appropriate testing, review and accountable release decisions.\nPeople management\nLead and develop a team of AI engineers through clear goals, work allocation, regular feedback and performance reviews.\nCoach technical and career development, address delivery blockers and foster strong team ownership.\nJob Requirements:\nBachelor's degree in Computer Science, Computer Engineering, Software Engineering, Data Science, Artificial Intelligence, or a related discipline.\n10+ years of technology/software engineering experience, including 5+ years of hands-on experience delivering AI/ML solutions, including production deployment of LLM-based applications or agents.\nStrong expertise in LLM engineering, including RAG, embeddings, structured outputs, tool calling and context engineering.\nStrong proficiency in Python and SQL, with experience in APIs, integrations, automated testing, Git, CI/CD, containers, authentication and production debugging.\nExperience with AI evaluation, failure analysis, reliability monitoring, data pipelines, databases, data quality and access-controlled retrieval.\nExperience with cloud deployment, relational and analytical data stores, model APIs, and delivery pipelines, with demonstrated ability to make sound architecture, technology, and operational decisions. Familiarity with equivalent technologies and frameworks is welcome.\nStrong understanding of machine learning and deep learning fundamentals, including transformers, embeddings, model validation and selecting between prompting, retrieval, fine-tuning and conventional ML.\nProven ability to translate business problems into measurable outcomes, lead technical architecture and delivery, establish engineering standards, and manage delivery across business, technology and security teams.\nExperience working with business users and product owners, and collaborating with data engineering, infrastructure, DevOps, security, architecture, and application teams to deliver and operate integrated solutions.\nProven track record in leading and developing AI engineering teams, including setting strategic goals, managing resources, developing talent, coaching engineers, and driving performance.\nExperience with PyTorch, open-weight models, MLOps, multimodal/document AI, MCP or major AI platforms such as Azure OpenAI, OpenAI, Anthropic, AWS or Google AI is advantageous.\nSkills\nGeneral Administration, Enterprise Integration Solution, Service Development, Medical Degree, Agents, scientific discipline, test measures, Develop reusable code, Computer Science, AI Evaluation, post delivery support, Embedding, Artificial Intelligence Application, Delivery Management, Context Engineering, Industry Experience","description_format":"text","description_chars":5148,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Telecommunications","Broadband"],"lifecycle":[{"event":"open","at":"2026-10-26T06:28:50Z"}],"visa":[],"liveness":{"score":84,"band":"hot","label":"Hiring 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