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AI Engineer
Интересная позиция в известном финтех-банке с фокусом на передовые технологии (Agentic AI). Высокий потенциал роста и работа над критически важными задачами в сфере управления рисками.
Сложность вакансии
Роль требует не только навыков разработки на Python, но и глубокого понимания современных LLM-фреймворков (LangGraph) и архитектуры агентных систем. Кандидату необходимо уметь работать на стыке инженерии данных и проектирования пользовательского опыта в контексте ИИ.
Анализ зарплаты
Зарплата в вакансии не указана, но для позиции AI Engineer в Сан-Франциско с опытом 2-5 лет рыночные показатели весьма высоки. Предлагаемый диапазон соответствует стандартам крупных технологических компаний и финтех-сектора США.
Сопроводительное письмо
I am writing to express my strong interest in the AI Engineer position at SoFi. With a solid background in software development and hands-on experience in building AI-powered applications, I am particularly drawn to your focus on agentic AI systems and LangGraph orchestration. My experience in designing multi-step reasoning workflows and integrating LLMs into production-grade services aligns perfectly with the goals of your Risk Analytics group.
In my previous roles, I have successfully bridged the gap between complex intelligence layers and intuitive user experiences. I am proficient in Python and have a deep understanding of context engineering, prompt design, and AI observability. I am excited about the opportunity to apply these skills within SoFi’s independent risk organization to build reliable, impactful AI systems that enhance risk management and internal workflows.
I am impressed by SoFi’s commitment to innovation and its member-first approach. I am eager to bring my ownership mindset and technical expertise to your team to help shape the next generation of financial services. Thank you for considering my application.
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Описание вакансии
Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
SoFi’s AI Engineer is a hands-on engineering role within SoFi’s growing independent risk organization, focused on building agentic AI systems to solve real-world, high-impact problems. This role will be instrumental in designing, prototyping, and deploying AI systems that enhance risk management and internal workflows.
This role sits at the intersection of the intelligence layer, including LLMs, agents, and orchestration, and the experience layer, which focuses on how users interact with and derive value from the AI systems developed. You will work closely with the Senior Manager of AI Engineering within the Risk Analytics group to build systems that are technically strong, intuitive, reliable, and impactful for end users.
What you’ll do:
- Architect and Develop Agentic AI Systems: Design, build, and orchestrate AI systems that leverage multi-step reasoning, tool use, and structured workflows, using frameworks such as LangGraph or similar approaches. Incorporate planning, memory, tool integration, and adaptive control flow to enable automated decisioning, risk insights, and internal platforms.
- Design the Experience Layer: Work closely with stakeholders to define how users interact with AI systems, including designing intuitive workflows, interfaces, and feedback loops that drive adoption and trust.
- Context Engineering and System Design: Structure inputs, outputs, and system context to improve reliability and performance of LLM systems, including prompt design, retrieval strategies, and workflow composition.
- Productionize AI Systems: Develop production-grade services and APIs, integrate agents into real systems, and ensure scalability, reliability, and maintainability.
- AI Observability and Evaluation: Build tracing, debugging, and evaluation frameworks to understand system behavior and continuously improve agent performance.
- Cross-Functional Collaboration: Partner with risk, engineering, and business teams to translate ambiguous problems into working AI systems and deliver measurable outcomes.
- Proof of Concepts and Innovation: Identify opportunities to automate workflows using AI, rapidly prototype solutions, and evaluate new tools and approaches by staying up-to-date with latest trends in AI
What you’ll need:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
- Two to five years of software development experience, with hands-on experience building and shipping AI-powered applications or workflows.
- Experience working with LLMs and building applications using prompting, APIs, or agent frameworks.
- Familiarity with agentic patterns such as tool use, multi-step reasoning, or workflow orchestration.
- Experience structuring inputs and outputs for LLM systems through context engineering, including prompt design and retrieval-based approaches.
- Experience building backend services and APIs, with Python preferred.
- Familiarity with cloud platforms such as AWS, Azure, or GCP and modern development practices.
- Experience working with data, including structured or unstructured data, and building pipelines for downstream applications.
- Understanding of how to evaluate AI systems, including defining success metrics and iterating based on performance.
- Strong problem-solving skills and the ability to work through ambiguous problems.
- Strong communication and collaboration skills, with the ability to work cross-functionally.
- An ownership mindset with a bias for action in building and shipping solutions.
Nice to have:
- Experience with frameworks for building agentic applications such as LangGraph.
- Experience designing user-facing workflows, internal tools, or applications powered by AI.
- Familiarity with observability tools for AI systems such as Langfuse / LangSmith
- Exposure to financial services or risk-related use cases.
- Experience with frontend technologies such as React for building AI-powered interfaces.
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
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Навыки
- Python
- LLM
- LangGraph
- Generative AI
- AWS
- Azure
- GCP
- API Development
- React
- LangSmith
- Langfuse
- Data Pipelines
Возможные вопросы на собеседовании
Проверка практического опыта работы с фреймворками для создания агентов, упомянутыми в вакансии.
Можете ли вы описать свой опыт работы с LangGraph или аналогичными инструментами для оркестрации многошаговых рассуждений ИИ?
Оценка понимания надежности и качества ответов LLM.
Какие стратегии вы используете для проектирования контекста и промптов, чтобы минимизировать галлюцинации и обеспечить структурированный вывод?
Важная часть вакансии — создание систем, которыми удобно пользоваться.
Как вы подходите к проектированию «слоя взаимодействия» (experience layer), чтобы пользователи доверяли решениям, принимаемым ИИ-агентом?
Проверка навыков мониторинга и улучшения систем в продакшене.
Какие метрики и инструменты обсервабильности (например, LangSmith) вы бы внедрили для оценки производительности агентной системы в реальном времени?
Оценка способности работать в условиях неопределенности, что указано в требованиях.
Расскажите о случае, когда вам пришлось переводить неоднозначную бизнес-задачу в техническое решение на базе ИИ. С какими трудностями вы столкнулись?
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