Who You Are
You are a Senior AI Engineer who designs, builds, and deploys enterprise-grade AI solutions, from LLM-based applications to intelligent automation and predictive models. You are proactive, comfortable proposing and validating ideas, and capable of influencing AI strategy across multiple initiatives. You thrive in a Microsoft/Azure ecosystem, work confidently in client-facing environments, and are motivated to grow from a senior individual contributor into a future technical leader.
What You’ll Do
- Design, develop, and deploy AI/ML solutions, including LLM-based applications, intelligent automation, and predictive models.
- Build scalable AI inference pipelines and integrate AI capabilities into enterprise applications.
- Leverage Azure AI services such as Azure OpenAI, Azure Machine Learning, and Cognitive Services.
- Propose and deliver AI proof-of-concepts, solution architectures, and innovation initiatives.
- Identify opportunities to improve productivity through AI-driven automation and reusable components.
- Implement CI/CD pipelines, monitoring, and engineering best practices using Azure DevOps.
- Collaborate directly with clients to understand business challenges and translate them into AI solutions.
- Present technical concepts, architectures, and results to both technical and non-technical stakeholders.
- Contribute to knowledge sharing, mentoring, and future team leadership initiatives.
What You Bring
- 5+ years of experience in AI/ML engineering, data science, or automation engineering.
- Advanced English (B2/C1) is mandatory, with strong verbal and written communication skills.
- Strong hands‑on experience with Azure cloud services and enterprise environments.
- Proficiency in Python with the ability to deliver production‑grade AI solutions.
- Practical experience with LLMs, embeddings, vector databases, prompt engineering, and generative AI.
- Solid understanding of model lifecycle management, data engineering, and MLOps practices.
- Ability to work autonomously, handle ambiguity, and take ownership of complex initiatives.
- Confidence engaging with clients as a trusted technical advisor.
Nice to Have
- Experience with AI agents, RPA, orchestration frameworks, or workflow automation tools.
- Exposure to the Microsoft 365 ecosystem (Graph API, SharePoint, Teams, Power Platform, etc.).
- Experience designing end‑to‑end AI architectures in large‑scale or enterprise settings.
- Familiarity with Responsible AI principles, security, and compliance best practices.
- Previous mentoring, technical leadership, or team enablement experience.