AI Solutions Engineer

Under the direct supervision of the Director of Practice & Business Systems, the AI Solutions Engineer is responsible for designing, developing, and deploying scalable enterprise AI and machine learning solutions to meet business objectives. Responsibilities: Build, deploy, and maintain enterprise-grade AI solutions using the Microsoft AI stack (Azure OpenAI Service, AI Foundry, Copilot Studio). Design agentic AI systems that integrate with enterprise services and data sources. Develop, fine-tune, and evaluate LLMs for instruction-following, retrieval-augmented generation (RAG), summarization, and other enterprise use cases. Implement vector search and retrieval pipelines to support RAG and contextual grounding. Collaborate with Practice Groups and Business Professionals to identify opportunities to automate business processes and enhance capabilities through AI and machine learning. Evaluate emerging AI technologies and recommend adoption strategies to improve business processes and outcomes. Monitor and maintain deployed AI solutions, ensuring high performance, reliability, and scalability. Collaborate with Network Systems, Information Security, and Electronic Information Governance teams to ensure all solutions comply with security, privacy, and governance standards. Ensure enterprise-grade security, privacy, and compliance standards are implemented across AI solutions. Follow established software development life cycle (SDLC) methodologies and best practices. Under the direct supervision of the Director of Practice & Business Systems, the AI Solutions Engineer is responsible for designing, developing, and deploying scalable enterprise AI and machine learning solutions to meet business objectives. Responsibilities: Build, deploy, and maintain enterprise-grade AI solutions using the Microsoft AI stack (Azure OpenAI Service, AI Foundry, Copilot Studio). Design agentic AI systems that integrate with enterprise services and data sources. Develop, fine-tune, and evaluate LLMs for instruction-following, retrieval-augmented generation (RAG), summarization, and other enterprise use cases. Implement vector search and retrieval pipelines to support RAG and contextual grounding. Collaborate with Practice Groups and Business Professionals to identify opportunities to automate business processes and enhance capabilities through AI and machine learning. Evaluate emerging AI technologies and recommend adoption strategies to improve business processes and outcomes. Monitor and maintain deployed AI solutions, ensuring high performance, reliability, and scalability. Collaborate with Network Systems, Information Security, and Electronic Information Governance teams to ensure all solutions comply with security, privacy, and governance standards. Ensure enterprise-grade security, privacy, and compliance standards are implemented across AI solutions. Follow established software development life cycle (SDLC) methodologies and best practices. Qualifications: Deep technical knowledge in AI/ML principles, scalable architectures, and cloud-based AI deployments. Expertise in developing solutions using Microsoft Azure OpenAI, AI Foundry, Cognitive Services, and related Azure AI technologies. 5+ years’ experience in Python or C#, RESTful API development, use of SDKs and ML frameworks (PyTorch, Transformers/Hugging Face). Experience with prompt engineering, LLM training and fine-tuning. Strong knowledge of responsible AI principles and ethical AI deployment. Experience integrating LLMs with enterprise data sources and services via APIs, connectors, and secure network architectures. Excellent communication and collaboration skills; able to lead projects and work independently or within a team. Bachelor’s degree from an accredited college in Computer Science, Engineering, or related field; Legal industry experience preferred. Qualifications: Deep technical knowledge in AI/ML principles, scalable architectures, and cloud-based AI deployments. Expertise in developing solutions using Microsoft Azure OpenAI, AI Foundry, Cognitive Services, and related Azure AI technologies. 5+ years’ experience in Python or C#, RESTful API development, use of SDKs and ML frameworks (PyTorch, Transformers/Hugging Face). Experience with prompt engineering, LLM training and fine-tuning. Strong knowledge of responsible AI principles and ethical AI deployment. Experience integrating LLMs with enterprise data sources and services via APIs, connectors, and secure network architectures. Excellent communication and collaboration skills; able to lead projects and work independently or within a team. Bachelor’s degree from an accredited college in Computer Science, Engineering, or related field; Legal industry experience preferred.

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