{"id":1239577,"url":"https://alion.io/job/dksh-ai-engineer-assistant-manager-evergreen","title":"AI Engineer, Assistant Manager (Evergreen)","company":{"id":20289,"name":"DKSH","domain":"dksh.com","url":"https://alion.io/company/dksh","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Kuala Lumpur, Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":52000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1271},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-09-08T00:00:00Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-09-25T19:02:56Z","board_verified":false,"closed_at":null,"days_open":20,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":20},"description":"About the Role\nThe AI Engineer (Machine Learning Operations), Assistant Manager, Group Digital Transformation is an individual contributor role responsible for engineering, deploying, and operating production-grade Artificial Intelligence (AI) and Machine Learning (ML) solutions at scale across DKSH. This role sits at the intersection of AI, software engineering, and cloud platforms, enabling faster time-to-value from AI investments by establishing robust ML Operations (MLOps) practices and automation that power revenue-generating and mission-critical AI use cases globally.\nWhat You Will Deliver\nDesign, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models in production, ensuring stable, reliable, and scalable performance.\nEngineer scalable model deployment architectures across cloud environments, including Microsoft Azure, to support both batch and real-time inference at enterprise scale.\nImplement automated workflows for model versioning, Continuous Integration and Continuous Deployment (CI/CD), rollback, and end-to-end lifecycle management.\nEnsure production AI systems consistently meet requirements for performance, reliability, security, and cost efficiency.\nMonitor models for data drift, performance degradation, and operational issues, and implement effective remediation strategies to sustain business continuity.\nPartner closely with AI Specialists, data scientists, and data engineers to successfully productionize models and analytics solutions.\nDevelop reusable components, frameworks, and templates that accelerate AI delivery across markets and use cases.\nIntegrate AI models into enterprise systems, digital products, and business workflows via Application Programming Interfaces (APIs) and services.\nSupport the deployment of generative AI and Large Language Model (LLM)-based solutions with appropriate guardrails, observability, and operational controls.\nDefine and enforce MLOps standards, best practices, and reference architectures to drive AI engineering maturity across DKSH.\nContribute to documentation, runbooks, and knowledge sharing to uplift AI engineering capability across teams.\nSupport audits, compliance, and responsible AI requirements from an engineering and operational perspective.\nAdministrative duties and coordination tasks as required.\nWhat You Bring\nBachelor's degree in Computer Science, Engineering, Data Science, or a related field; relevant cloud, DevOps, or AI engineering certifications are an advantage.\nMinimum 5 years of experience in AI engineering, MLOps, DevOps, or software engineering roles, with demonstrated experience supporting production AI or data-driven systems at scale.\nStrong hands-on experience in MLOps, AI engineering, or machine learning platform roles.\nProficiency in Python and software engineering best practices.\nHands-on experience with Databricks and MLFlow for model deployment and lifecycle management.\nPractical experience with CI/CD pipelines and automation for AI/ML workloads.\nExperience with cloud platforms, preferably Microsoft Azure, including Azure Machine Learning (Azure ML), Azure DevOps, and container technologies.\nStrong understanding of the machine learning lifecycle, encompassing training, inference, monitoring, and retraining.\nExperience with containerization and orchestration tools such as Docker and Kubernetes.\nFamiliarity with infrastructure-as-code and platform automation practices.\nExposure to generative AI and Large Language Model (LLM) deployment patterns.\nExperience working in agile or product-oriented delivery teams.\nAbility to engineer reliable, secure, and scalable systems in complex enterprise environments.\nStrong problem-solving mindset with close attention to operational detail.\nAbility to influence stakeholders and communicate effectively with both technical and non-technical audiences to drive cross-functional collaboration.\nWhy Join DKSH\nAt DKSH, we help companies grow in Asia and enable people to perform at their best. You will be part of an organization that values accountability, collaboration, and long-term partnerships. We offer a dynamic environment where your contributions are visible and where you can build a meaningful career in Digital Transformation.\n#LI-KP1","description_format":"text","description_chars":4264,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Wholesale","Pharmaceutical Distribution","Medical Equipment Distribution"],"lifecycle":[{"event":"open","at":"2026-09-25T16:35:49Z"}],"liveness":{"score":72,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.797,"p_room":0.9,"age_days":19,"expected_fill_days":30,"reasons":["conf:34","velocity","win:mid","comp:brand"],"computed_at":"2026-09-27T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/dksh-ai-engineer-assistant-manager-evergreen","json_url":"https://alion.io/job/dksh-ai-engineer-assistant-manager-evergreen.json","meta":{"generated_at":"2026-09-28T01:13:47Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":795,"day_limit":5000,"remaining_today":4205,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}