- Страна
- США
- Зарплата
- 108 000 $ – 170 000 $
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на вакансии с ИИ

AI Agent Engineer
Отличная вакансия в быстрорастущей AI-компании с прозрачным диапазоном зарплаты и сильным стеком технологий. Высокий балл за счет сочетания инновационного продукта, хорошего соцпакета и возможности влиять на конечный результат.
Сложность вакансии
Роль требует редкого сочетания навыков: глубокой экспертизы в LLM/RAG, опыта работы с телефонией (SIP/PSTN) и готовности к активному общению с клиентами. Высокая сложность обусловлена необходимостью вести проект от разработки промптов до интеграции в сложные корпоративные экосистемы.
Анализ зарплаты
Предложенный диапазон ($108k - $170k) полностью соответствует рыночным стандартам для AI Engineer в США, особенно учитывая удаленный формат и дополнительные бонусы в виде опционов. Верхняя граница диапазона конкурентоспособна даже для технологических хабов.
Сопроводительное письмо
I am writing to express my strong interest in the AI Agent Engineer position at Observe.AI. With over three years of experience in building and deploying conversational AI solutions, I have developed a deep expertise in prompt engineering, RAG architectures, and complex system integrations. My background in Python and experience with orchestration frameworks like LangChain align perfectly with your mission to deliver enterprise-grade AI agents.
In my previous roles, I have successfully led the end-to-end lifecycle of AI products, from initial API configurations to telephony setup using Twilio and Amazon Connect. I am particularly drawn to Observe.AI because of your focus on predictable outcomes and natural conversations for enterprises like DoorDash. I am confident that my technical skills in LLM optimization and my ability to lead client-facing demos will allow me to contribute immediately to your implementation team.
I am excited about the opportunity to help Observe.AI's clients transform their customer experiences. Thank you for considering my application. I look forward to the possibility of discussing how my technical background and problem-solving mindset can support your team's goals.
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Описание вакансии
About Us
Observe.AI is the leading AI agent platform for customer experience. It enables enterprises to deploy AI agents that automate customer interactions, delivering natural conversations for customers with predictable outcomes for the business.
Observe.AI combines advanced speech understanding, workflow automation, and enterprise-grade governance to execute end-to-end workflows with AI agents. It also enables teams to guide and augment human agents with AI copilots, and analyze 100% of human and AI interactions for insights, coaching, and quality management.
Companies like DoorDash, Affordable Care, Signify Health, and Verida use Observe.AI to transform customer experiences every day by accelerating service speed, increasing operational efficiency, and strengthening customer loyalty across every channel.
Why Join Us
We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization.
You’ll own the end-to-end lifecycle of AI agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance.
What you’ll be doing
- Build & Deploy Agents: Own the full AI agent build process - prompts, workflows, integrations, telephony setup, and evaluation forms.
- Client Engagement: Lead weekly demos, show progress, gather feedback, and act as the primary technical point of contact once a solution is defined.
- Systems Integration: Configure APIs, data maps, authentication, error handling, and connect to CRMs, databases, or knowledge systems.
- Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality.
- Optimization: Monitor performance, refine prompts, test iteratively, and ensure agents meet automation and containment targets.
- Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion.
- Shadow Core Engineering: Collaborate with product/engineering teams for deep technical fixes and platformization, while independently leading client delivery.
What you'll bring to the role
- 3+ years in conversational AI, ML engineering, or system integration with hands-on delivery of AI/LLM-based solutions.
- Strong skills in prompt engineering, workflow building, API integration, and telephony (SIP, Twilio, Amazon Connect, etc.).
- Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.).
- ML expertise in embeddings, retrieval-augmented generation (RAG), evaluation frameworks, fine-tuning models, and performance optimization.
- Solid programming skills (Python, JavaScript, or similar).
- Comfort leading customer-facing discussions - from deep technical troubleshooting to weekly project demos.
- Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field
- Hands-on experience with Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficient in API integrations and data flow management.
- Strong experience in telephony integrations, including knowledge of protocols like SIP, PSTN, and other telephony technologies.
Perks & Benefits
- Competitive compensation including equity
- Excellent medical, dental, and vision insurance options
- Flexible time off
- 10 Company holidays + Winter Break and up to 16-weeks of parental leave
- 401K plan
- Quarterly Lifestyle Spend
- Monthly Mobile + Internet Stipend
- Pre-tax Commuter Benefits
Salary Range
The base salary compensation range targeted for this full-time position is $108 - 170Kper annum. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives and equity (in the form of options). This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices.
Our Commitment to Inclusion and Belonging
Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.
We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply.
If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visitwww.observe.ai.
#LI- Redwood City, CA (Hybrid)
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Навыки
- Python
- JavaScript
- LLM
- Generative AI
- Prompt Engineering
- RAG
- LangChain
- LlamaIndex
- SIP
- Twilio
- Amazon Connect
- API Integration
- Vector Databases
- n8n
- Zapier
Возможные вопросы на собеседовании
Проверка практического опыта работы с RAG и понимания ограничений контекста.
Расскажите о самом сложном случае внедрения RAG: как вы решали проблемы с качеством извлечения данных и галлюцинациями модели?
Вакансия требует настройки SIP и CCaaS, что критично для голосовых ИИ-агентов.
С какими трудностями вы сталкивались при интеграции ИИ-агентов с телефонией (например, Twilio или Amazon Connect) и как вы обеспечивали низкую задержку (latency)?
Роль предполагает ведение еженедельных демо для клиентов.
Как вы объясняете технические ограничения LLM (например, вероятность ошибки) нетехническим заказчикам, сохраняя их доверие к продукту?
Проверка навыков работы с инструментами автоматизации рабочих процессов.
Каков ваш опыт работы с iPaaS-платформами (n8n, Zapier) для построения цепочек действий ИИ-агента?
Оценка навыков оптимизации и оценки качества.
Какие метрики и фреймворки вы используете для оценки эффективности работы ИИ-агента перед его запуском в продакшн?
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- Страна
- США
- Зарплата
- 108 000 $ – 170 000 $