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Senior Software Engineer - AI Coding Agents
Отличная вакансия в крупной публичной компании (NICE), работающей на острие технологий ИИ-агентов. Высокий балл обусловлен использованием самого современного стека (Next.js, Vercel AI SDK) и масштабом задач, влияющих на Fortune 100 компании.
Сложность вакансии
Роль требует глубоких знаний как в современном full-stack стеке (Next.js, TypeScript), так и в специфических ИИ-технологиях (Vercel AI SDK, MCP, RAG). Высокая сложность обусловлена необходимостью проектировать автономных агентов и интегрировать их в сложные корпоративные инфраструктуры.
Анализ зарплаты
Предлагаемая роль Senior уровня в США в сфере AI/Cloud обычно оплачивается выше среднего по рынку из-за дефицита специалистов на стыке Full-stack и AI Engineering. Указанный диапазон соответствует стандартам крупных технологических хабов, таких как Сиэтл и Атланта.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Software Engineer position for AI Coding Agents at NICE. With over 5 years of experience in full-stack development and a deep focus on the TypeScript/React ecosystem, I have closely followed the evolution of agentic workflows and LLM integrations. My background in building scalable cloud applications, combined with hands-on experience using the Vercel AI SDK and implementing RAG pipelines, aligns perfectly with your mission to transform cloud operations through intelligent automation.
In my previous roles, I have specialized in bridging the gap between complex backend logic and intuitive frontend interfaces. I am particularly excited about NICE's focus on moving AI beyond simple chatbots into production-grade operational tools that integrate with systems like Jira and ServiceNow. I am eager to bring my expertise in Next.js, prompt engineering, and distributed systems to help build the next generation of AI-driven platforms that your 25,000+ global customers rely on.
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Описание вакансии
At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.
AI Software Engineer – Cloud AI Platforms
At NICE, we are not just building software—we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you’re excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.
What’s the role all about?
As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.
This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments.
How will you make an impact?
- Build and scale AI-driven workflows and automation systems
- Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
- Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
- Work on LLM integrations, prompt engineering, and orchestration layers — streaming responses, function calling, tool use, RAG pipelines, agentic orchestration
- Build and maintain full-stack AI applications using TypeScript, React, and Next.js — from user dashboards and personalized experiences to real-time analytics and interactive tools
- Translate real-world operational problems into automated, intelligent solutions
- Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
- Improve system performance, reliability, and observability
- Build evaluation and observability systems — measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
- Create reusable platforms and tools that accelerate development — component libraries, shared abstractions, internal tooling that multiplies team productivity
Key Responsibilities
- Design and develop scalable backend systems for AI-powered platforms
- Build and maintain AI integrations, workflows, and automation pipelines
- Implement REST APIs, microservices, and event-driven architectures
- Design and implement database schemas and queries for complex domains — tracking, engagement, reporting
- Work with both structured and unstructured data for AI use cases
- Contribute to CI/CD pipelines, testing, and deployment automation
- Troubleshoot and optimize production systems
- Collaborate with cross-functional teams to deliver high-quality solutions
- Contribute to reusable frameworks and engineering best practices
- Prototype fast — move from concept to working demo in days, ship incrementally
What we’re looking for
- 5+ years of software engineering experience, strong focus on full-stack web development
- Expert in TypeScript and React — performance optimization, modern patterns (hooks, context, suspense), component architecture
- Production experience with Next.js — App Router, Server Components, API routes, SSR/SSG, edge deployment
- Hands-on experience with LLMs — prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
- Experience with Vercel AI SDK — unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
- Model Context Protocol (MCP) — building or consuming MCP servers for extensible AI tool use
- Strong backend fundamentals — Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
- Solid database design — PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
- Experience building scalable, distributed systems in cloud environments (AWS / Azure)
- Working knowledge of CI/CD, Docker, Kubernetes
- Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
- High agency — you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
- Strong problem-solving and analytical skills
- Ability to work in a fast-paced, evolving environment
- Communicate effectively with both technical and non-technical stakeholders
Nice to have
- Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
- Experience with Vercel ecosystem — Next.js, AI SDK providers, Turbopack
- Background in evaluation frameworks — measuring model capabilities, collecting human feedback at scale, A/B testing outputs
- Experience with sandboxed execution environments for safely running AI-generated code
- Built research tools, experimentation platforms, or scientific software
- Proficiency with Python — FastAPI/Django, data pipelines, ML tooling
- Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
- Experience building automation or internal platforms
- Familiarity with real-time features — WebSockets, streaming UX, collaborative interfaces
- Knowledge of advanced web technologies — WebGL, WebAssembly, web workers, PWAs
- Experience with alternate JS runtimes — Bun, Deno
- Built open-source tools or platforms with active user communities
- Strong quantitative foundation (math, physics, or related fields)
Representative Projects
Things you might build in this role:
- Interfaces for collecting and managing human feedback on model outputs at scale
- Experiment orchestration platforms — launch, monitor, and analyze complex AI research runs
- Visualization tools that help understand model behavior and identify failure modes
- Reusable components and frameworks that enable rapid development of new AI applications
- Sandboxed execution environments for safely running AI-generated code
- AI-powered personalization engines — tutoring, content generation, adaptive features
- Workflow builders that let non-engineers orchestrate AI capabilities visually
- Enterprise integrations — ServiceNow, Salesforce, Confluence, Jira
*About NiCE*
NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.
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Навыки
- TypeScript
- React
- Next.js
- Node.js
- Python
- LLM
- Prompt Engineering
- RAG
- PostgreSQL
- Redis
- AWS
- Azure
- Docker
- Kubernetes
- Tailwind CSS
- Radix UI
- GraphQL
- REST
- Drizzle ORM
Возможные вопросы на собеседовании
Проверка практического опыта работы с LLM в продакшене.
Расскажите о вашем опыте работы с потоковой передачей ответов (streaming) и вызовом функций (function calling) в LLM. С какими основными проблемами вы сталкивались?
Оценка навыков проектирования сложных систем.
Как бы вы спроектировали систему оценки (evaluation framework) для измерения качества ответов ИИ-агента в реальном времени?
Проверка владения современным стеком Next.js.
В чем преимущество использования Server Components и App Router в Next.js при создании интерфейсов для ИИ-приложений?
Безопасность и надежность ИИ-решений.
Какие подходы вы используете для безопасного выполнения сгенерированного ИИ кода в изолированных средах (sandboxed environments)?
Проверка soft skills и самостоятельности.
Опишите ситуацию, когда вам приходилось работать в условиях высокой неопределенности (ambiguous environment). Как вы расставляли приоритеты?
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