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Senior AI Engineer – Technical Enablement
УдалённоПолная занятостьAI EngineeringSemiconductor Manufacturing
Develop and deploy secure AI tools, agent workflows, and intelligent automations that integrate with enterprise systems. Improve AI adoption through documentation, training, feedback, and responsible governance.
Обязанности
- Build and deploy AI tools, agents, and workflows using automation platforms.
- Integrate AI agents with enterprise systems, external APIs, and knowledge bases.
- Identify repetitive work and design intelligent process automations.
- Implement encryption, authentication, authorization, and identity integrations using standards and platforms such as OAuth2, OIDC, SAML, Entra ID, and AD FS.
- Partner with cybersecurity teams on data protection, threat modeling, governance, and compliance.
- Create documentation and deliver internal training to improve AI literacy.
- Collect user feedback, iterate on solutions, and scale successful implementations.
Требования
- Bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, data science, or a related field, or equivalent experience.
- At least 5 years of software development experience, including 2 or more years in AI or machine learning engineering.
- Strong knowledge of AI concepts, machine learning pipelines, and automation tools.
- Hands-on experience with Copilot Studio, UiPath, and SharePoint.
- Experience with multi-agent workflows, retrieval-augmented generation, semantic chunking, memory persistence, prompt engineering, and context-window optimization.
- Knowledge of MCP-based context-aware systems, agent orchestration, and agent-to-agent systems.
- Experience with Azure AI Foundry, AWS Bedrock, and/or Google Vertex AI.
- Proficiency in .NET, C#, Python, Java, API development, SQL, PowerShell, and Unix shell scripting.
- Strong problem-solving, agile delivery, and cross-functional communication skills.
Будет плюсом
- Exposure to generative AI, prompt engineering, or agent-based systems.
- Interest in AI governance, security, and ethical frameworks.
- Ability to deliver rapid improvements while maintaining enterprise standards.