4 дня назад
Forward Deployed AI Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Forward Deployed AI Engineer (Generative AI/Agentic Systems): Building and deploying full-stack AI applications for strategic enterprise customers with an accent on foundation models, RAG, semantic search, and scalable enterprise architectures. Focus on moving prototypes toward production, designing LLMOps/MLOps practices, and translating customer needs into repeatable AI solution patterns.
Location: Remote in Australia, Sydney
Company
provides an enterprise data platform that helps organizations transform complex data into actionable insights, with a focus on open-source technologies and applied AI.
What you will do
- Build and prototype full-stack AI applications and agentic systems on the platform.
- Work directly with strategic customers to move AI and agentic use cases from early prototypes toward production readiness.
- Advise technical and executive stakeholders on AI roadmaps, use-case prioritization, deployment, and business alignment.
- Turn successful implementations into reusable reference architectures, productized solutions, starter kits, and internal playbooks.
- Mentor internal teams and share customer feedback with product teams to improve AI platforms and products.
Requirements
- 5+ years of experience building and deploying production-grade systems, including 2–3 years developing generative AI or agentic applications.
- Strong software engineering, data engineering, and applied AI/ML skills, including full-stack AI application development.
- Experience with foundation models, context engineering, fine-tuning, semantic search, RAG, and agentic workflows.
- Deep understanding of LLMOps/MLOps, including evaluation, observability, serving, monitoring, and lifecycle management.
- Experience designing scalable AI architectures that meet enterprise security, governance, and compliance standards.
- Ability to work directly with technical and executive customers, operate autonomously, and translate business needs into technical strategy.
Nice to have
- Experience with AWS, Azure, or GCP.
- Experience with the platform and open-source big data technologies such as Spark, Iceberg, or NiFi.
- Experience with NVIDIA GPUs, inference optimization, model serving, or distributed AI workloads.
Culture & Benefits
- Flexible work-from-home policy and support for work-life balance.
- Generous paid time off and additional Unplugged Days.
- Mental and physical wellness programs.
- Phone and internet reimbursement.
- Career development opportunities, comprehensive benefits, paid volunteer time, and employee resource groups.
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