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About the role
Senior Software Engineer - Applied AI at Microsoft
Required Skills
pythonc#azureai/mlllmsmlopsdockerkubernetesgenai
About the Role
Senior Software Engineer - Applied AI role at Microsoft's Dynamics 365 Contact Center team. Responsibilities include designing and building intelligent, scalable AI solutions integrated into enterprise software, collaborating with cross-functional teams, and ensuring production reliability and performance.Key Responsibilities
- Design and develop scalable application capabilities integrating AI models
- Translate business requirements into AI solutions with cross-functional teams
- Optimize AI model performance and reliability in production environments
- Own deployment, quality, and operation of AI systems with MLOps/DevOps practices
- Troubleshoot live site issues and ensure high reliability and performance
Required Skills & Qualifications
Must Have:
- Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages like C, C++, C#, Java, JavaScript, or Python OR equivalent experience
- 4+ years of experience with customers success, zero trust security and compliance
- 4+ years of experience with coding, debugging, and problem-solving skills
- Ability to meet Microsoft, customer and/or government security screening requirements including Microsoft Cloud Background Check
Nice to Have:
- Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience OR Bachelor's Degree AND 8+ years technical engineering experience OR equivalent experience
- 3+ years of experience with GenAI, Large Language Models (LLM), or agentic systems
- Experience with Speech-to-Text services
- AI & Domain Expertise: Deep expertise in one or more AI domains with a proven track record of deploying and scaling AI models in cloud environments
- MLOps & LLMOps: Experience with MLOps workflows and familiarity with modern LLMOps frameworks
- Cloud & Infrastructure: Skilled in building and operating infrastructure using Azure, AWS, or Google Cloud, and deploying containerized models with Docker, Kubernetes, or similar tools
Benefits & Perks
- Industry leading healthcare