Senior AI Engineer (Agentic Systems / LLMs / Python) · LATAM\n\n- Location:\nAnywhere in LATAM\n- Job Type:\nRemote\n- Project:\nFintech Conversational AI Platform\n- Time Zone:\nFlexible within LATAM\n- English Level:\nB2 / C1\n\n_______________________________________________\nDisclaimer – Must read: Commitment & Focus\nThis role requires full-time dedication, with clear priority given to Darwoft projects during the established working hours.It is not compatible with other full-time professional engagements.Any additional professional activities must be disclosed in advance and must not interfere with the responsibilities or working hours of this role.\nGet to Know Us\nAt Darwoft, we create software that drives real change. But we're more than just tech — we're people first. We believe in building human-centered digital experiences and having fun while we do it.\nOur team is curious, passionate, and always growing. Based in Latin America, we partner with companies worldwide to develop innovative solutions with purpose.\nWe work remotely, collaboratively, and with a strong sense of community — always embracing continuous learning, adaptability, and real impact.\nAbout the Role\nWe're looking for a\nSenior AI Engineer\nto join a high-impact fintech project focused on building next-generation conversational AI systems.\nThis is not a traditional chatbot role.\nYou'll be working on\nproduction-grade agentic systems\n, evolving AI from simple interactions into\nautonomous, multi-agent architectures\ncapable of reasoning, planning, and executing complex workflows across critical business domains.\nYou'll operate close to the core AI strategy, collaborating with product and engineering teams to bring intelligent systems into real-world production environments — with direct impact on thousands of users.\nWhat You'll Be Doing\n\n- Design, build, and deploy\nstateful AI agents\nusing Python and modern agentic frameworks (LangGraph, CrewAI, etc.)\n- Develop\nmulti-agent systems\ncapable of handling complex, multi-step workflows with reasoning and planning\n- Implement and optimize\nRAG pipelines\nusing vector databases for accurate and grounded outputs\n- Integrate AI agents into\ncore product infrastructure\n(APIs, internal services, business workflows)\n- Build\nLLMOps capabilities\n, including monitoring, tracing, and observability of agent behavior (reasoning paths, latency, tool usage)\n- Design advanced\nevaluation pipelines (evals-as-code)\nusing techniques like LLM-as-a-judge, semantic similarity, and adversarial testing\n- Optimize systems for\nperformance and cost efficiency\n(prompt optimization, caching, model routing)\n- Ensure production readiness through\nCI/CD pipelines, containerization (Docker/Kubernetes), and system reliability practices\n- Collaborate with cross-functional teams to translate business needs into scalable AI solutions\n- Mentor and contribute to best practices in\nAI engineering and software craftsmanship\n\nWhat You Bring\n\n- 7+ years of experience in software engineering\n- 2+ years building\nAI / Generative AI systems in production\n- Strong proficiency in\nPython\n- Hands-on experience with\nLLM frameworks and APIs\n(OpenAI, LangChain, LlamaIndex, CrewAI, or similar)\n- Proven experience designing\nagentic systems\n(multi-agent workflows, memory/state management)\n- Solid experience with\nRAG architectures and vector databases\n- Strong understanding of\nsoftware engineering fundamentals\n(Git, testing, CI/CD)\n- Experience integrating AI into\nreal production environments\n, not just prototypes\n- Ability to translate business problems into scalable technical solutions\n- Strong communication skills in a remote, English-speaking environment\n\nNice to Have\n\n- Experience in fintech, payments, fraud, or financial platforms\n- Experience with\nLLMOps tools\n(LangSmith, Arize, Weights & Biases, etc.)\n- Experience with\nevaluation frameworks and benchmarking for LLM systems\n- Background in\ncost optimization of AI systems at scale\n- Contributions to open-source or public AI projects\n- Experience working in\nhigh-growth, fast-paced environments\n\nPerks & Benefit