{"id":2614537,"url":"https://alion.io/job/svitla-systems-senior-data-engineer-3","title":"Senior Data Engineer","company":{"id":2216,"name":"Svitla Systems","domain":"svitla.com","url":"https://alion.io/company/svitla-systems","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","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":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AR","MX","CR"],"hiring_countries_total":3,"salary":null,"salary_estimate":{"min_usd":90000,"max_usd":204000,"period":"year","method":"global_role_seniority_cell","sample_n":2324},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-15T11:28:23Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-16T11:38:46Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Svitla Systems Inc. is looking for a Senior Data Engineer for a full-time position (40 hours per week) in LATAM. Our client is a US-based fintech company that runs a community finance platform where members can borrow and lend small amounts to cover emergency expenses. Launched in 2018, it offers an alternative to payday loans, with borrowers setting their own terms, along with financial education and digital banking services. The platform serves around 2 million users and has facilitated about $1 billion in transactions.\nOur client is building the data function of the future: one professional operating a team of AI agents rather than managing a team of people. In this builder-operator role, you will own data science, analysis, business intelligence, risk, fraud, and data engineering across the client’s ecosystem, using agents as the workforce and your judgment as the control layer. You will design the pipelines, systems, and evaluation standards that turn transaction and behavioral data into signals the business can act on, while keeping data quality, lending risk, and fraud detection sharp end to end.\nRequirements\n5+ years as a data or software engineer shipping production systems (not just analysis or reporting).\nStrong Python fundamentals and systems-design judgment, plus deep fluency in SQL and data warehousing.\nHands-on experience directing AI agents or LLM-based workflows in production, not just experimenting with them.\nA portfolio, GitHub history, or shipped systems that you can point to and discuss in depth.\nComfort operating with high autonomy and full ownership.\nWill be a plus\nRisk and fraud analytics experience in fintech, lending, or payments.\nCredit scoring or alternative underwriting background.\nTrack record of building evaluation or observability systems for ML or agent pipelines.\nBackground in consumer fintech or marketplaces.\nExperience working in a high-pace, high-accountability environment.\nResponsibilities\nOrchestrate AI agents across the full data lifecycle, from ingestion and pipeline health to modeling and reporting, while owning the code and architecture they touch.\nBuild and refine evaluation harnesses that keep agent output accurate and auditable.\nWrite and review production Python and SQL for pipelines, services, and models.\nMake systems-design decisions on how data infrastructure scales.\nMonitor scoring model performance, default and delinquency trends, and fraud signals, intervening when human judgment must lead.\nStand up dashboards and BI that give the team a live view of marketplace health.\nPartner with product and risk to ship data-informed decisions 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