4 дня назад
Lead AI Engineer
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead AI Engineer (GenAI/Python): Leading the design and delivery of scalable, production-ready generative AI systems with an accent on RAG pipelines, agentic frameworks, and LLMOps. Focus on architectural guidance, model optimization, responsible AI, observability, and mentoring cross-functional engineering teams.
Location: Singapore, Singapore; on-site. Applicants must be Singapore Citizens due to project requirements and client security clearance.
Company
is a technology consultancy delivering software and technology solutions to help clients solve complex business problems.
What you will do
- Lead cross-functional teams of software engineers, data scientists, and other specialists delivering generative AI solutions.
- Guide the design and delivery of scalable, reliable, production-ready AI-powered systems.
- Set technical direction and provide architectural guidance, balancing experimentation with short, safe delivery cycles.
- Collaborate with product managers, designers, business partners, and stakeholders to align technical solutions with business goals.
- Establish engineering practices for testing, guardrails, responsible AI, monitoring, documentation, and observability.
- Review designs and code, optimize GenAI applications for accuracy, performance, and cost, and determine when model tuning is required.
Requirements
- Strong expertise in Python and modern software engineering practices, including CI/CD, testing, version control, and system reliability.
- Experience designing and integrating end-to-end AI systems for scalability, maintainability, and performance.
- Deep experience with generative AI and agentic frameworks, RAG pipelines, vector databases, and production deployments.
- Experience deploying AI solutions on major cloud platforms using containers and reproducible CI/CD pipelines.
- Experience with LLMOps, production monitoring, observability tools, fine-tuning, model adaptation, and ML/NLP frameworks.
- Ability to communicate complex technical concepts, influence senior decision-makers, and mentor high-performing engineering teams.
Culture & Benefits
- Career development supported through interactive tools, development programs, and peer guidance.
- Autonomy combined with a collaborative cultivation culture.
- Inclusive environment focused on continuous learning and knowledge sharing.
- Responsible AI practices are applied to recruitment systems, including testing, monitoring, and bias mitigation.
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