{"id":2842665,"url":"https://alion.io/job/dbs-assoc-ai-core-devops-engineer-data-platform-group-technology","title":"Assoc, AI Core DevOps Engineer, Data Platform, Group Technology","company":{"id":451141,"name":"DBS","domain":"dbs.com","url":"https://alion.io/company/dbs-4","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":249,"ghost_share":0,"stale_share":0.731,"repost_share":0,"time_to_fill_p50_days":40,"computed_at":"2026-10-23T05:54:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","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":null,"salary_estimate":{"min_usd":46000,"max_usd":112000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":28},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"ArgoCD","optional":false},{"name":"Bootstrap","optional":false},{"name":"Chart.js","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Django","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"GitOps","optional":false},{"name":"Google ADK","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google GKE","optional":false},{"name":"Grafana","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"IAM","optional":false},{"name":"JavaScript","optional":false},{"name":"KServe","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"MySQL","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Presto","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Recharts","optional":false},{"name":"SQL","optional":false},{"name":"styled-components","optional":false},{"name":"Trino","optional":false},{"name":"Triton","optional":false},{"name":"Vertex AI","optional":false},{"name":"Vertex AI Agent Builder","optional":false},{"name":"vLLM","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-10-14T00:00:00Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-22T01:51:37Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"Job Responsibility\nWorking with subject-matter experts (SMEs) across finance, infrastructure, security, risk, and application teams, you will learn their processes and constraints to design AI and agent-based solutions that give the organisation clear, actionable insight. We want a resource who takes full ownership of their work and is keen to learn how enterprise architecture comes together.\nEnterprise 360° AI Initiative\nWork with SMEs across domains to map their current processes, data sources, pain points, and limitations.\nTurn business needs into AI and agentic use cases, then propose, prototype, and refine solutions with the team.\nDevelop AI models for cost forecasting, anomaly detection, utilisation right-sizing, and compliance risk scoring.\nDesign and build AI agents that can answer questions, summarise posture, flag issues, and recommend or trigger actions (for example, \"Which applications are over-provisioned and missing DR coverage?\").\nPut guardrails, evaluation, human-in-the-loop approvals, and audit trails in place so agents are safe and trustworthy at enterprise scale.\nTurn successful prototypes into reusable, production-grade services and reference patterns.\nFull-Stack Application Development\nBuild and maintain interactive 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example vLLM, Triton, or KServe) and Vertex AI endpoints.\nIntegrate with GitOps (ArgoCD or Flux) and observability platforms (Prometheus, Grafana, Cloud Monitoring, OpenTelemetry).\nApply security and compliance standards across all deployments.\nOwnership & Execution\nOwn your deliverables end to end: plan, build, document, hand over, and support them.\nTake initiative, raise risks early, suggest improvements, and follow through without being asked.\nKeep up with developments in AI, agents, and infrastructure, and bring useful ideas back to the team.\nJob Requirements\n3-6 years of experience in DevOps, platform, MLOps, or AI engineering.\nHands-on experience building ML models or LLM-based applications in Python.\nExposure to RAG pipelines, vector databases, LLM evaluation, and guardrails.Exposure to agentic frameworks and patterns such as LangGraph, Google ADK, Vertex AI Agent Builder, CrewAI, tool/function calling, or MCP.\nExperience building interactive web applications with 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