{"id":837995,"url":"https://alion.io/job/dlocal-staff-ai-engineer-ai-labs","title":"Staff AI Engineer - AI Labs","company":{"id":6586,"name":"dLocal","domain":"dlocal.com","url":"https://alion.io/company/dlocal","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":78,"open_postings":24,"ghost_share":0.292,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":131,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Madrid, Spain","Buenos Aires, Argentina","Barcelona, Spain","Bucharest, Romania","Montevideo, Uruguay","Brazil"],"countries":["ES","AR","RO","UY","BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":78000,"max_usd":178000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1279},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false}],"status":"live","first_seen_at":"2026-09-10T09:05:31Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-11-02T08:11:43Z","board_verified":true,"closed_at":null,"days_open":53,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":52},"description":"What's the Opportunity?\nYou will join the AI Lab, a team whose mission is to validate high-value emerging AI and automation technologies and de-risk their adoption across dLocal. This is a rare opportunity to work at the frontier of applied AI in fintech: running rigorous experiments on the latest models and tools, and turning results into decisions that shape how a global payments company adopts AI.\nThis is a senior individual-contributor role. It does not require direct people management, but it carries significant technical influence within the Lab and across the teams that consume its work.\nAs a Staff AI Engineer in the AI Lab, you own technology scouting, prototyping, and evaluation for dLocal. You will run instrumented spikes and benchmarking on emerging AI technologies, produce clear recommendations for stakeholders across engineering, business, legal and IT based on your prototypes, and coordinate hand-offs to the teams that take validated technologies into production.\nFor promising technologies, you will help define the patterns, guardrails, and technical requirements needed for adoption and coordinate the hand-off to the engineering teams responsible for productionizing them.\nWhat will I be doing?\nTechnology Scouting & Evaluation\nRun short, instrumented spikes and benchmarking on new models, tools and frameworks: LLMs, agentic systems, vector databases, orchestration frameworks, copilots, assistants and more.\n\nCompare vendor and open-source options, documenting trade-offs across quality, cost, latency, security and integration complexity.\n\nDeliver concise decision memos with clear recommendations: adopt, watch, or avoid.\n\nEvaluation Harnesses & Sandboxes\nDesign and maintain evaluation environments (e.g. datasets, prompts, scenarios, telemetry) to test models under realistic constraints.\n\nBuild automation and tooling to measure quality, robustness, latency and cost, including regression tracking over time.\n\nEnsure every evaluated technology has benchmark coverage and a documented risk and limitations view.\n\nPrototyping & Technical Validation\nBuild enough of a system to understand how a technology behaves under realistic conditions, not just in vendor demos or isolated examples.\n\nExplore architecture, integration patterns, operational constraints, security boundaries, and failure modes through working prototypes.\n\nDetermine what must be true for a proof of concept to become a viable production capability.\n\nPrefer focused prototypes that answer specific technical questions over prematurely building production systems.\n\nRecommendations, Readiness & Hand-offs\nTranslate technical findings into clear decision memos for both technical and non-technical stakeholders.\n\nFor validated technologies, produce readiness guidance covering recommended patterns, guardrails, known limitations, operational considerations, and integration requirements.\n\nCoordinate hand-offs to the engineering teams responsible for productionization.\n\nSupport those teams during the transition when deep context from the evaluation is required, without becoming the permanent owner of the resulting system.\n\nTrack what happens after Lab recommendations and use those outcomes to improve future evaluation methods.\n\nGovernance, Risk & Standards\nWork with Security, Legal, Compliance and other AI teams to document risk assessments, mitigations and governance recommendations for each evaluated technology.\n\nMaintain checklists, decision templates and lightweight standards reusable across evaluations and by partner teams.\n\nIncorporate learnings from third-party AI tooling already in use, such as external copilots and the AWS AI suite, into adoption guidelines.\n\nCollaboration, Mentoring & Community\nPartner with other AI teams and domain teams to ensure clear boundaries and smooth collaboration.\n\nParticipate in hiring as a technical evaluator and culture champion.\n\nMentor engineers in the Lab and adjacent teams on evaluation methods, benchmarking and experimental design.\n\nShare knowledge through internal write-ups, tech talks and occasional external meetups and conferences.\n\nWhat skills do I need?\nTechnical depth\n8+ years of software engineering experience, including significant experience operating at senior or Staff-level scope.\n\nDeep hands-on experience building and evaluating systems based on LLMs and modern AI tooling.\n\nStrong software engineering fundamentals and the ability to rapidly build high-quality experimental systems.\n\nExperience building agentic or multi-step AI systems involving tool use, orchestration, state, retrieval, or external integrations.\n\nStrong knowledge of cloud infrastructure, preferably AWS, and the ability to run experimental workloads securely and cost-consciously.\n\nExperience with observability, telemetry, testing, and benchmarking of complex systems.\n\nAbility to reason about system architecture, reliability, scalability, asynchronous workflows, and distributed components where relevant.\n\nTrack record of designing experiments or benchmarks that influenced meaningful technical decisions.\n\nBenchmarking & evaluation\nTrack record designing and running benchmarks that compare AI models and tools under real constraints.\n\nExperience constructing evaluation datasets: task selection, labelling, holdout discipline, and keeping a set useful as models improve.\n\nWorking knowledge of LLM-as-judge methods and their failure modes, alongside human evaluation, inter-annotator agreement, and a view on when each is appropriate.\n\nAble to reason about statistical significance on small samples, and to state confidence honestly rather than over-reading a result.\n\nFamiliarity with regression tracking, telemetry and versioning, so that a result stays reproducible months later.\n\nDecision-making\nAble to turn ambiguous \"we should try this new thing\" ideas into well-scoped evaluation plans with clear hypotheses and metrics.\n\nComfortable making trade-off calls across quality, latency, cost and vendor lock-in, and documenting them clearly.\n\nExperience writing short, opinionated decision memos that help others move fast.\n\nCollaboration & communication\nCan explain technical results to non-specialists in concrete, concise terms.\n\nExperience working with platform, product and operations teams to align evaluations with real use cases.\n\nAble to influence without authority, aligning teams around shared standards and guardrails.\n\nMindset\nCurious and biased toward experimentation, combined with disciplined measurement and risk awareness.\n\nComfortable in a small, high-leverage team without embedded PMs. You structure your own work and keep stakeholders informed.\n\nBuilder attitude: you prefer reusable tools, templates and playbooks over one-off work.","description_format":"text","description_chars":6723,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Spain","iso":"ES","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Payment Processing & Gateways","Currency Exchange & FX Payments"],"lifecycle":[{"event":"open","at":"2026-09-12T20:00:34Z"}],"visa":[],"liveness":{"score":77,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":0.9,"age_days":52,"expected_fill_days":131,"reasons":["conf:2","win:mid"],"computed_at":"2026-11-02T06:13:15Z"},"pay":null,"html_url":"https://alion.io/job/dlocal-staff-ai-engineer-ai-labs","json_url":"https://alion.io/job/dlocal-staff-ai-engineer-ai-labs.json","meta":{"generated_at":"2026-11-02T10:18:29Z","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":14366,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-03T00:00:00Z"}},"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":6586},"rest":"https://alion.io/mcp/rest/get_company?id=6586"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fdlocal-staff-ai-engineer-ai-labs"},{"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%2Fdlocal-staff-ai-engineer-ai-labs"},{"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%2Fdlocal-staff-ai-engineer-ai-labs"},{"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/dlocal-staff-ai-engineer-ai-labs\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fdlocal-staff-ai-engineer-ai-labs"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":837995}},{"tool":"search_jobs","arguments":{"company":"dlocal.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":837995},"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. Docs: https://alion.io/developers"}}