AI enablement engineer in property management

ОнТаргет ЛАБС; United States; A distancia; USD 150.000 - 190.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Удаленная работа

Descripción de la vacante

Компания ОнТаргет ЛАБС в США ищет практичного инженера по AI‑enablement для реализации практических AI‑потоков в разработку и поддержку DX/CI/CD. Вы будете проектировать инструкции агентов, паттерны и навыки, а также обучать команду на регулярных сессиях.

Требуется 7+ лет опыта в инженерии ПО, владение Claude Code, Warp и LLM‑API, а также глубокое понимание процессов разработки и развёртывания. Удаленная работа и конкурентная компенсация.

Formación

• Глубокий практический опыт использования AI-инструментов в инженерной работе.
• Опыт создания повторяемых рабочих процессов, интеграций и шаблонов агентов.
• Понимание CI/CD, обзора качества и производственной поддержки.
• Умение обучать инженеров: демонстрации, парное обучение, документация.
• Умение управлять безопасностью, стоимостью и операционными рисками.

Responsabilidades

• Устанавливать практические AI‑потоки для кодирования, отладки, тестирования, планирования и дизайна.
• Разрабатывать инструкции агентов, паттерны запросов и навыки, совместно с Platform Lead.
• Связывать AI‑workflow с CI/CD, песочницами, тестированием и DX‑сигналами.
• Создавать валидационные циклы для проверки вывода AI через тесты и ревью.
• Проводить обучение инженерам через демо-сессии, парное программирование и офис‑часы.
• Разрабатывать повторяемые паттерны для AI‑помощников и внутренних возможностей.

Conocimientos

Английский язык (уровень общения)

7+ лет опыта в разработке ПО

AI-интеграции в разработку

CI/CD / DX

Коучинг инженеров

Educación

Бакалавр в информационных системах/компьютерных науках

Herramientas

Claude Code

Warp

AI-агенты

LLM APIs

MCP workflows

Descripción del empleo

Описание:

A fast-growing B2B SaaS platform in the US property management industry. Our platform supports complex multi-tenant workflows, integrations, payments, and operational processes that real businesses rely on every day. As we grow, we are investing in AI-first engineering, developer experience, and modern engineering foundations so product teams can ship faster, safer, and with more confidence. We are looking for a hands-on AI enablement engineer to make AI-assisted delivery practical, repeatable, trusted, and tied to real engineering outcomes.

Задачи:

Establish practical AI-first workflows for coding, debugging, testing, planning, design, docs, reviews, and production investigation. Build reusable agent instructions, prompt patterns, skills, repo context, integrations, and examples that teams can apply directly. Partner with the Platform Lead to connect AI workflows with CI/CD, sandboxes, parallel agent workflows, testing, observability, release readiness, and DX signals. Create validation loops so AI output can be checked through tests, reviews, quality signals, security controls, and release checks. Coach engineers through demos, pairing, docs, examples, office hours, and practical workflow design. Shape reusable patterns for AI-powered product and internal capabilities, including assistants, retrieval, automation, governance, access, and reuse. Use adoption, quality, productivity, cost, and delivery signals to prioritize work and measure real leverage.

Требования:

Excellent verbal and written communication skills in English 7+ years of software engineering experience preferred, with strong senior-level candidates considered; experience improving DevEx, platform capabilities, internal tooling, engineering productivity, or AI enablement is especially relevant. Deep hands-on use of AI tools for real engineering work, especially Claude Code, Warp, AI agents, LLM APIs, MCP workflows, or similar tools. Strong engineering depth, with experience building reusable workflows, integrations, reference implementations, prompts, agent skills, evaluation patterns, and automation. Practical understanding of planning, implementation, testing, reviews, CI/CD, release readiness, production support, and documentation. Strong judgment around AI output quality, validation, testing, reviewability, security, privacy, cost, and operational risk. Ability to drive adoption through coaching, examples, documentation, pairing, workshops, office hours, or enablement programs. Practical AI-first mindset focused on measurable engineering outcomes. Bachelor’s degree in Information Systems, Computer Science, or a related field Claude Code, Warp, AI coding agents, LLM-based developer workflows, or similar tools. Agent SDKs/APIs from Anthropic, OpenAI, AWS Bedrock, or similar platforms. MCP servers, tool calling, agent workflows, reusable instructions, prompt patterns, skills, or orchestration. Depth in at least one modern engineering language, such as Python, TypeScript, Go, C#, .NET, or similar. RAG, semantic search, knowledge agents, embeddings, vector databases, or retrieval patterns. Git workflows, CI/CD, test automation, code review, release readiness, and developer productivity tooling. AWS, cloud environments, containers, or sandbox-style execution environments. Observability, evaluation, monitoring, logging, tracing, cost tracking, and quality measurement. Security, access control, privacy, auditability, and governance for internal and product-facing AI systems. Будет плюсом: Sandboxed or cloud-based agent execution, parallel AI workflows, or human-as-orchestrator patterns; AI-powered SaaS features, internal knowledge-base agents, Slack agents, or employee AI assistants; Legacy modernization in a mature production SaaS environment; Fintech, payments, accounting, eCommerce, property management, or other transactional domains; Security, compliance-aware delivery, data access controls, or regulated environments

Условия:

• Competitive compensation to be defined upon the interview results
• Full time REMOTE WORK