{"id":3393191,"url":"https://alion.io/job/websparks-mlai-engineer-fraud-analytics-model-public-sector","title":"ML/AI Engineer - Fraud Analytics Model (Public Sector)","company":{"id":252555,"name":"Websparks","domain":"websparks.sg","url":"https://alion.io/company/websparks","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"contractor","work_mode":"hybrid","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":8000,"max":12000,"currency":"SGD","period":"month","gross":true,"usd_annual":112428},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Incident Management","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Amazon S3","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"GitHub Actions","optional":true},{"name":"Jenkins","optional":true},{"name":"LangChain","optional":true},{"name":"MLFlow","optional":true},{"name":"RAG","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-28T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-28T00:00:00Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"1-year contract, renewable\nGovernment project\nHybrid work arrangement\nRole Overview\nThe ML/AI Engineer will join the Fraud Analytics Model (FAM) team within the Data Analytics and AI Division (DSAD). The role supports FAM 2.0, which detects misuse of public training subsidies, by designing and building two agentic AI systems.\nOne system will surface emerging fraud risks and blind spots. The other will help turn validated risks into actionable detection logic. Human validation, evaluation and responsible AI guardrails will be built into both systems.\nYou will deliver working, evaluated minimum viable products (MVPs) and help build DSAD’s in-house capability to operate and maintain them independently.\nKey Responsibilities\nAgentic AI architecture: Design the end-to-end architecture for FAM agentic AI solutions, including agent orchestration, workflows, state management, tool integration, human approval points and system interactions. Use suitable frameworks such as LangGraph or CrewAI. Architecture decisions will be made in consultation with DSAD’s Platform Team.\n\nEmerging-risk agent development: Develop AI agents that analyse approved information sources to identify, generate and prioritise evidence-linked emerging fraud and abuse risks for officer review.\n\nDetection engineering agent development: Develop AI agents that assess data feasibility, propose candidate risk indicators and detection features, and support the translation of validated risks into actionable analytics and detection logic.\n\nData and analytics integration: Integrate agent workflows with FAM 2.0 data and analytics components, including Redshift, Glue and PySpark. Build and maintain the data preparation and feature engineering processes needed to support AI and ML workloads.\n\nProduction engineering: Turn prototypes into modular, tested, maintainable and deployable services, workflows, APIs or agentic applications, with clear interfaces, version control and operational ownership.\n\nCI/CD and automation: Build automated workflows to test, validate and promote code, prompts, workflows and AI components across environments. Include quality, security and human approval gates where required.\n\nEvaluation and AI guardrails: Implement evaluation frameworks and governance controls covering output quality, reproducibility, traceability, access control, exception handling, human approval and safeguards against untrusted inputs, such as prompt injection.\n\nMonitoring and reliability: Implement observability, dashboards and alerts for system health, latency, throughput, errors, resource use, data quality, workflow performance and operating costs. Support incident management, troubleshooting and root-cause analysis.\n\nDomain collaboration: Work closely with DSAD data scientists, business users and analysts to capture domain expertise, refine agent workflows and ensure solutions address operational fraud-detection needs.\n\nDocumentation and knowledge transfer: Produce maintainable code, architecture decision records, evaluation evidence, operational runbooks and technical documentation. Conduct knowledge transfer to support the long-term sustainability of the solutions.\n\nRequirements and Qualifications\nEducation and ExperienceEducation: Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related technical discipline.\n\nExperience: 3–5 years of hands-on experience building and deploying ML/AI applications, including at least one LLM-enabled system delivered beyond the prototype stage into operational use.\n\nEssential Technical and Professional CompetenciesStrong Python software engineering skills, including API development, testing, version control and modular system design.\n\nHands-on experience building and deploying ML/AI applications, including at least one LLM-enabled or agentic AI solution beyond the proof-of-concept stage.\n\nExperience with LLM applications, retrieval, tool use, workflow orchestration or multi-agent frameworks such as LangGraph, CrewAI or equivalent.\n\nExperience integrating AI/ML solutions with enterprise data platforms, databases, APIs or cloud services.\n\nAbility to design and implement systematic evaluation frameworks for AI systems, including testing, benchmarking, observability and reproducibility.\n\nWorking knowledge of AI governance, security and responsible AI practices, including human-in-the-loop controls, access management, auditability and safeguards against misuse.\n\nStrong problem-solving and analytical skills, with the ability to translate business requirements into scalable AI-enabled solutions.\n\nPreferred ExperienceExperience with AWS services such as Bedrock, Redshift, Glue, S3, Lambda or related cloud-native services.\n\nExperience with PySpark, Databricks, large-scale data processing or feature engineering pipelines.\n\nExperience with CI/CD, containerisation, MLOps or model deployment tools such as Docker, MLflow, GitHub Actions or Jenkins.\n\nExperience implementing monitoring, observability and operational support processes for ML/AI applications.\n\nExperience delivering fraud-detection, risk, compliance, investigation or decision-support solutions.\n\nExperience with knowledge retrieval, retrieval-augmented generation (RAG), graph-based workflows, prompt management, model evaluation tools or AI observability platforms.\n\nFamiliarity with Singapore Government or public-sector technology environments, including data governance, security and compliance requirements.\n\nExperience working with cross-functional teams of data scientists, engineers, analysts and business stakeholders.\n\nSoft Skills and CommunicationStrong engineering judgement and a structured approach to experimentation, with the ability to distinguish a robust MVP from a demonstration.\n\nAbility to explain architecture, evaluation evidence, risks and controls to technical, governance and management audiences.\n\nCollaborative approach to working with fraud-domain officers. You will design systems that capture their expertise while keeping decisions and accountability with them.\n\nAbility to integrate quickly into an existing team and work effectively with limited supervision.\n\nComfort working across research, engineering, integration, documentation and stakeholder engagement.\n\n/Ref: 309\n\nSkills\nAPI Development, Multi-Agent Systems, Fraud Investigation Planning and Execution, Agent Orchestration, Technical Skills, LangGraph, Risk Monitoring, Data Solutions, Artificial Intelligence, Platform Architecture, Computer Science, Version Control Systems, Fraud Analytics, Cloud Services, User Acceptance Testing, Education, CrewAI","description_format":"text","description_chars":6636,"description_truncated":false,"requirements":{"experience_years_min":3,"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":["Government","Fraud Detection"],"lifecycle":[{"event":"open","at":"2026-10-28T10:28:00Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.542,"p_room":1,"age_days":1,"expected_fill_days":30,"reasons":["seen:1","agency","velocity","win:early"],"computed_at":"2026-10-29T05:49:05Z"},"pay":{"stated_usd_annual":112428,"is_top_pay":false},"html_url":"https://alion.io/job/websparks-mlai-engineer-fraud-analytics-model-public-sector","json_url":"https://alion.io/job/websparks-mlai-engineer-fraud-analytics-model-public-sector.json","meta":{"generated_at":"2026-10-29T20:56:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":31043,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-30T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":252555},"rest":"https://alion.io/mcp/rest/get_company?id=252555"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fwebsparks-mlai-engineer-fraud-analytics-model-public-sector"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fwebsparks-mlai-engineer-fraud-analytics-model-public-sector"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fwebsparks-mlai-engineer-fraud-analytics-model-public-sector"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/websparks-mlai-engineer-fraud-analytics-model-public-sector\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fwebsparks-mlai-engineer-fraud-analytics-model-public-sector"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3393191}},{"tool":"search_jobs","arguments":{"company":"websparks.sg","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3393191},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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