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Senior Staff Software Engineer, AI Accelerated SDLC
Это престижная позиция в ведущем финтех-банке США с возможностью определять технологический стек будущего. Высокий балл обусловлен фокусом на инновационном направлении (AI SDLC) и значительным влиянием роли на всю компанию.
Сложность вакансии
Роль Senior Staff уровня требует не только глубоких технических знаний в области ИИ и облачных технологий, но и выдающихся лидерских качеств для влияния на всю инженерную организацию. Высокая сложность обусловлена необходимостью интеграции новейших ИИ-агентов в устоявшиеся процессы разработки крупного банка.
Анализ зарплаты
Указанная роль Senior Staff в США/Канаде обычно предполагает компенсацию выше среднего по рынку, учитывая дефицит специалистов на стыке Platform Engineering и AI. Предлагаемый диапазон соответствует топовым технологическим компаниям.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Staff Software Engineer position within the Builder Tools organization at SoFi. With over 8 years of experience in software development and a deep focus on AI-driven developer productivity, I am excited about the opportunity to lead the architecture of your next-generation AI-powered SDLC. My background in building scalable cloud-native systems on AWS, combined with hands-on expertise in agentic frameworks like LangChain and tools like AWS Bedrock, aligns perfectly with SoFi's mission to elevate the developer experience.
In my previous roles, I have successfully led initiatives to automate complex workflows and integrate AI assistants into the coding and deployment process. I am particularly drawn to SoFi's forward-thinking approach to financial services and your commitment to innovation. I am confident that my technical leadership and passion for mentoring can help scale the adoption of AI-powered tooling across your engineering organization, driving both operational excellence and developer satisfaction.
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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:
We are looking for an experienced Senior Staff Software Engineer to join our Builder Tools engineering organization with a mission to enable SoFi engineers to elegantly solve problems. In this role, you will have the opportunity to directly impact, influence and lead the direction and architecture of our next gen AI-powered SDLC, and elevate developer experience through AI enabled workflows, tooling and practices. You will get the chance to lead, define, and take on complex and interesting problems as part of a fast-paced, highly collaborative organization. The ideal candidate will be a mentor, technical leader and a team player who is hands-on and comfortable driving solutions from initial architecture to implementation and adoption with a strong sense of ownership and drive for delivery.
What You’ll Do:
- Technical leadership - Provide thought leadership for technical architecture and design, implementation, delivery and operations of AI enabled tools, agents, and workflows across the SDLC including plan, code, test, build, deploy, observe and remediate.
- Innovate - Collaborate with cross-functional teams to drive innovation in developer tooling, and advancements including AI assisted developer productivity flows.
- Exemplary Practitioner -Be a subject matter expert for one or more developer tooling domains, including operational excellence.
- Mentor - Collaborate with engineers in the team, provide mentorship, and domain expertise to enhance the overall technical capabilities of the team..
- Continuous Improvement - Contribute to creating a culture of continuous learning, data-driven decisions and improvements. Proactivelyidentify and manage risks.
- Collaborate –Build strong working relationships with coworkers and cross-organizational teams.
- Influence - Influence and scale the adoption of AI powered SDLC tooling, workflows and best practices across the engineering organization.
What You’ll Need:
- Experience - Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.
- 8+ years software development experience.
- Experience developing in a cloud environment (ex: AWS), using containers (e.g., Docker, Kubernetes), cloud-native technologies, service meshes (e.g., Istio, Envoy), CI/CD and automated testing.
- Expertise - 2+ years of experience in AI tools (e.g., Claude Code, Agent SDK, Prompts, Skills, Cursor), infrastructure (e.g., MCP, AWS Bedrock, RAGs, vector dbs) and agent frameworks (e.g. Langchain, Langgraph, CrewAI)
- Design - Strong understanding of software design principles, and distributed systems architecture.
- Problem solving - Strong problem solving and programming fundamentals (algorithms, data structures).
- Coding Skills - Proven coding skills (e.g., Java, Kotlin, Python) delivering large scale systems with infrastructure automation (e.g., Terraform).
- Project Ownership - Ability to own, manage and deliver projects from scoping through launch. Experience working with Agile development processes.
- Strong Interpersonal skills - Excellent written and verbal communication skills. Demonstrated ability to collaborate well with technical and non-technical members, and proven skills to operate effectively in a cross-functional team.
Preferred Qualifications:
- Experience with security, compliance, and risk management in cloud environments.
- Experience with monitoring and logging (e.g. Datadog, Elastic, Splunk).
- Experience with container orchestration (e.g., Docker, Kubernetes) and networking
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
- Java
- Kotlin
- Python
- AWS
- Docker
- Kubernetes
- Terraform
- LangChain
- AWS Bedrock
- Istio
- Envoy
- CI/CD
- Datadog
- Vector Databases
Возможные вопросы на собеседовании
Проверка опыта проектирования сложных систем, интегрирующих ИИ в процесс разработки.
Опишите архитектуру AI-агента, которого вы бы спроектировали для автоматизации процесса код-ревью в крупной организации. Какие метрики успеха вы бы использовали?
Оценка практических знаний в области LLM и инфраструктуры.
В чем заключаются основные сложности при внедрении RAG (Retrieval-Augmented Generation) для внутренней технической документации компании, и как бы вы их решали?
Проверка навыков лидерства и влияния на культуру разработки.
Как вы будете убеждать команды разработчиков внедрять новые ИИ-инструменты, если они опасаются за безопасность или качество кода?
Оценка опыта работы с облачной инфраструктурой и автоматизацией.
Расскажите о вашем опыте использования Terraform и Kubernetes для развертывания масштабируемых ИИ-сервисов. С какими узкими местами вы сталкивались?
Проверка способности решать проблемы на стыке ИИ и SDLC.
Как обеспечить воспроизводимость и надежность ИИ-инструментов в CI/CD пайплайне, учитывая стохастическую природу больших языковых моделей?
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