{"id":1555587,"url":"https://alion.io/job/shield-ai-engineer","title":"AI Engineer","company":{"id":2035147,"name":"SHIELD","domain":"shield.com","url":"https://alion.io/company/shield-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"C","score":62,"open_postings":19,"ghost_share":0.632,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-03T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"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":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Go","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Anthropic","optional":true},{"name":"Claude","optional":true},{"name":"Gemini","optional":true},{"name":"Git","optional":true},{"name":"Memcached","optional":true},{"name":"MySQL","optional":true},{"name":"OpenAI","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true},{"name":"Structured Outputs","optional":true}],"status":"live","first_seen_at":"2025-10-16T00:00:00Z","employer_posted_date":"2025-10-16","last_verified_at":"2026-10-03T23:16:49Z","board_verified":true,"closed_at":null,"days_open":353,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":352},"description":"SHIELD is a device-first fraud intelligence platform that helps digital businesses worldwide eliminate fake accounts and stop all fraudulent activity.\nPowered by SHIELD AI, we identify the root of fraud with the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence, empowering businesses to stay ahead of new and unknown fraud threats.\nWe are trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, TrueMoney, and more. With offices in LA, London, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.\nResponsibilities\nAs an AI Engineer, you will work closely with the team to build and enhance AI-powered systems that support proactive identification of fraudulent behavior across our clientele's platforms. This is an opportunity to be part of a high-impact team that combines data, AI, and engineering to protect ecosystems.\nBuild and maintain AI-powered systems for proactive fraud detection, including LLM-based and agentic workflows.\nDesign and implement RAG pipelines that ground models in SHIELD's fraud intelligence and data signals.\nDevelop and iterate on prompts and evaluations to ensure reliable, measurable model performance.\nRapidly prototype and ship new AI features, moving quickly from idea to production.\nExplore and integrate new data signals and model capabilities to improve fraud identification accuracy.\nConduct comprehensive testing to ensure system reliability, performance, and cost-efficiency.\nWrite clear documentation for systems, prompts, workflows, and research findings.\nCollaborate closely with engineers and analysts to achieve shared project goals.\nRequirements\nBachelor's Degree in Computer Science or a related field (or equivalent practical experience).\nStrong proficiency in Python (Go/Golang is a plus).\nHands-on experience building with LLM APIs such as OpenAI, Anthropic (Claude), or Google Gemini - including prompting, RAG, or agentic workflows.\nExperience building and shipping production software, with a bias for moving fast.\nExperience working with relational databases (e.g., MySQL, PostgreSQL).\nFamiliarity with version control systems (e.g., Git).\nIt will be good to have:\nExperience with vector databases or embedding-based retrieval.\nExperience designing structured outputs from LLMs (e.g., JSON or schema-constrained generation).\nFamiliarity with token optimization and cost/latency tuning.\nFamiliarity with evaluation frameworks or methods for LLM outputs.\nExperience working with caching systems (e.g., Redis, Memcached).\nPrior experience in the fraud detection or risk domain.","description_format":"text","description_chars":2669,"description_truncated":false,"requirements":{"experience_years_min":null,"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":["Commerce","E-commerce Platforms","Consumer Internet Groups"],"lifecycle":[{"event":"open","at":"2026-10-01T01:52:36Z"}],"visa":[],"liveness":{"score":3,"band":"cold","label":"Long shot","p_open":1,"p_active":0.09,"p_room":0.28,"age_days":352,"expected_fill_days":21,"reasons":["conf:24","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/shield-ai-engineer","json_url":"https://alion.io/job/shield-ai-engineer.json","meta":{"generated_at":"2026-10-04T00:18:48Z","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":268,"day_limit":5000,"remaining_today":4732,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}