Senior AI Engineer - Deep Learning Frameworks

As a Senior AI Engineer with 8-10 years of experience in software development, including 3+ years of hands-on experience delivering AI/ML solutions in production environments, you will play a key role in building and deploying generative AI solutions. Your responsibilities will include leading end-to-end delivery of AI-powered solutions across cross-functional teams. Key Responsibilities: - Build and deploy generative AI solutions using OpenAI compatible APIs - Lead end-to-end delivery of AI-powered solutions across cross-functional teams - Utilize advanced proficiency in Python for AI/ML development, experimentation, and automation - Work with deep learning frameworks such as PyTorch, TensorFlow, and Scikit Learn - Implement RAG architectures, including vector databases and semantic search - Utilize Azure OpenAI, LLM Gateway, Azure Functions, Azure Monitor, and Application Insights - Work with cloud-based AI and data services, including Databricks - Implement Azure Document Intelligence, OCR pipelines, and enterprise document processing - Apply expertise in agentic AI frameworks, AI Foundry patterns, LangFuse style observability, and enterprise search - Utilize NLP, Speech AI, Vision AI, and both supervised and unsupervised machine learning techniques - Collaborate with GitHub and M365 Copilot in modern development workflows Qualifications Required: - Experience in publishing research or contributing to open source AI initiatives - Designing AI systems for regulated or enterprise environments - Understanding of AI governance, responsible AI practices, and compliance frameworks - Experience mentoring technical teams or leading research initiatives In addition to your technical skills and qualifications, you are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of your day-to-day responsibilities. This includes consistent use of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise, leveraging AI tools to enhance coding, documentation, data analysis, and decision-making workflows, and staying current with evolving AI capabilities and features to improve delivery quality and velocity. As a Senior AI Engineer with 8-10 years of experience in software development, including 3+ years of hands-on experience delivering AI/ML solutions in production environments, you will play a key role in building and deploying generative AI solutions. Your responsibilities will include leading end-to-end delivery of AI-powered solutions across cross-functional teams. Key Responsibilities: - Build and deploy generative AI solutions using OpenAI compatible APIs - Lead end-to-end delivery of AI-powered solutions across cross-functional teams - Utilize advanced proficiency in Python for AI/ML development, experimentation, and automation - Work with deep learning frameworks such as PyTorch, TensorFlow, and Scikit Learn - Implement RAG architectures, including vector databases and semantic search - Utilize Azure OpenAI, LLM Gateway, Azure Functions, Azure Monitor, and Application Insights - Work with cloud-based AI and data services, including Databricks - Implement Azure Document Intelligence, OCR pipelines, and enterprise document processing - Apply expertise in agentic AI frameworks, AI Foundry patterns, LangFuse style observability, and enterprise search - Utilize NLP, Speech AI, Vision AI, and both supervised and unsupervised machine learning techniques - Collaborate with GitHub and M365 Copilot in modern development workflows Qualifications Required: - Experience in publishing research or contributing to open source AI initiatives - Designing AI systems for regulated or enterprise environments - Understanding of AI governance, responsible AI practices, and compliance frameworks - Experience mentoring technical teams or leading research initiatives In addition to your technical skills and qualifications, you are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of your day-to-day responsibilities. This includes consistent use of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise, leveraging AI tools to enhance coding, documentation, data analysis, and decision-making workflows, and staying current with evolving AI capabilities and features to improve delivery quality and velocity.