{"id":1478845,"url":"https://alion.io/job/silver-dev-carefull-data-scientist-ai-engineer","title":"Carefull - Sr. AI Engineer","company":{"id":8709,"name":"Silver.dev","domain":"silver.dev","url":"https://alion.io/company/silver-dev","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":79,"open_postings":7,"ghost_share":0,"stale_share":0.857,"repost_share":0,"time_to_fill_p50_days":46,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["AR"],"hiring_countries_total":1,"salary":{"min":60000,"max":78000,"currency":"USD","period":"year","gross":null,"usd_annual":78000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"DynamoDB","optional":false},{"name":"Langfuse","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Anomaly Detection","optional":true}],"status":"live","first_seen_at":"2026-09-29T15:37:52Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-01T10:58:49Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Carefull\nCarefull is an AI-powered financial safety platform that helps banks, credit unions, and wealth advisors protect older-adult customers from fraud and money mistakes. We help financial institutions maintain whole-family relationships while protecting their clients. Carefull’s technology addresses senior-specific financial safety challenges: our monitoring detects fraud patterns missed by industry-standard tools, and our features - identity-theft protection, password and document management, communication tools, and how-to content - help customers maintain financial independence while enabling loved ones to step in when needed.\nThe Role\nWe are looking for a Senior AI Engineer to join our Data team and build, evaluate, and improve the AI-powered systems at the core of our product. A big part of the work is detection: systems that analyze financial transactions and decide whether to alert a family that something concerning may be happening with their loved one's money. You'll also dig into user behavior and patterns, including how people interact with the product, and use what you learn to shape what we build next. This is a hands-on role. You'll research fraud patterns, design detection logic, write production code, and rigorously evaluate system performance. You'll own features end to end: from understanding a problem, to implementing and deploying a solution, to measuring whether it actually works.\nHow We Work\nOwnership here means caring about the outcome, not only the delivery. We work in small, fast increments, because a focused change in front of users today teaches us more than a complete one next week. You'll have a lot of autonomy in how you approach problems, and we trust people to find the next step on their own. When you're stuck, a quick question is always welcome, and short, frequent updates go a long way on a remote team. We use AI coding tools heavily and expect you to as well. We also expect you to understand what you ship and to be able to explain the reasoning behind every change.\nWhat You’ll Do\nDesign and ship new AI-driven detection features, from first prototype to production.\n\nBuild data enrichment pipelines that extract structured information from messy, real-world financial transaction data.\n\nResearch fraud and scam typologies relevant to older adults, and translate that understanding into detection logic that works at scale.\n\nBuild reproducible evaluations (test sets, metrics, error analysis) so every change can be measured against the last one.\n\nInvestigate issues reported by users or surfaced in production, find the root cause quickly, and ship the fix.\n\nOptimize AI pipelines for accuracy, latency, and cost, making informed tradeoffs about model selection and system architecture.\n\nWork with Customer Care, Go-to-Market, and partner-facing teams to understand what real users need.\n\nKeep up with new developments in LLMs and agents, and find practical ways to use them here.\n\nWho You Are\nRequired\nStrong Python skills, with experience building data pipelines and production systems.\n\nHands-on experience building LLM applications in production: prompting, structured outputs, context management, and working directly with provider SDKs and APIs.\n\nComfort deploying and operating what you build on a cloud platform.\n\nA habit of measuring before claiming something works. You know how to set up an evaluation, read precision and recall, and dig into errors until you understand them.\n\nA track record of owning work end to end without close supervision.\n\nReal curiosity about the domain. You'll want to understand how the US financial system works, how money moves between accounts, and how scammers take advantage of it.\n\nComfort reasoning about ambiguity. Our domain is full of cases where the answer depends on context, and you need to build systems that handle that.\n\nClear written and verbal communication in English. You'll document your reasoning, present to stakeholders, and explain technical decisions to non-technical teammates.\n\nStrong Plus\nAWS experience (Lambda, CDK, Bedrock, Redshift, DynamoDB).\n\nExperience with LLM observability and tracing tools such as Langfuse or LangSmith.\n\nBackground in fraud detection, fintech, or risk and compliance.\n\nExperience with financial transaction data (ACH, Zelle, wires, card payments).\n\nExperience working with regulated institutions such as banks\n\nNice to Have\nExperience working with regulated industries or bank partners.\n\nExposure to elder care, aging-in-place, or financial vulnerability research.\n\nBackground in data science or ML beyond LLMs (statistical modeling, anomaly detection).\n\nInterview Process\nSilver Screening interview\n\nTake-home challenge\n\nClient technical interview\n\nCTO interview\n\nFinal interview Hiring Manager","description_format":"text","description_chars":4766,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate (B2)","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Argentina","iso":"AR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Financial Services"],"lifecycle":[{"event":"open","at":"2026-09-29T19:31:35Z"}],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.542,"p_room":1,"age_days":1,"expected_fill_days":46,"reasons":["conf:5","agency","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":78000,"is_top_pay":false},"html_url":"https://alion.io/job/silver-dev-carefull-data-scientist-ai-engineer","json_url":"https://alion.io/job/silver-dev-carefull-data-scientist-ai-engineer.json","meta":{"generated_at":"2026-10-01T19:35:01Z","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":2220,"day_limit":5000,"remaining_today":2780,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}