Lead AI Solution Engineer

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Job Description:

The Impact You'll Make in this Role

As an AI Engineer, you will be instrumental in designing, developing, and deploying AI-driven applications that enhance our product offerings. This role emphasizes the practical application of AI technologies to solve complex business challenges, focusing on integrating AI capabilities into scalable and reliable systems. You will collaborate closely with cross-functional teams to ensure seamless integration of AI solutions into our products.

Key Responsibilities:

• Build full-stack AI applications, including Retrieval-Augmented Generation (RAG), AI agentic systems, and intuitive UI/UX interfaces for user-centric experiences.
• Develop AI-driven features using pre-trained models, APIs, prompt engineering, and custom integrations to meet specific business needs.
• Evaluate, select, and fine-tune large language models (LLMs) and other AI models, balancing performance, scalability, accuracy, and resource constraints.
• Optimize AI models and algorithms to enhance efficiency, reduce latency, and ensure scalability for production deployments.
• Collaborate closely with product managers, software engineers, data scientists, and project managers to translate AI capabilities into innovative solutions.
• Stay current with the latest advancements in AI technologies, practices, tools, and methodologies to continuously advance organizational capabilities.

To set you up for success in this role from day one, 3M requires (at a minimum) the following qualifications:

• Bachelor's degree in computer science, Artificial Intelligence, Data Science, or a related field.
• 5+ years of experience building full-stack AI applications, including at least 1 year specifically in Generative AI.
• Proven expertise in AI applications, including RAG solutions, AI agentic systems, and UI/UX design.
• Experience evaluating, fine-tuning, and deploying large language models (LLMs) such as GPT, Claude, or similar LLMs.
• Strong skills in prompt engineering, fine tuning to optimize AI model accuracy and relevance, perform benchmarking evaluations, and conduct model comparisons.
• Demonstrated ability to optimize AI models for cost`, scalability, and low-latency performance.

Additional qualifications that could help you succeed even further in this role include:

• Excellent communication and collaboration skills with product managers, data scientists, engineers, and stakeholders.
• Familiarity with MLOps practices, including model lifecycle management and CI/CD.
• Experience deploying AI applications on cloud platforms (AWS, Azure, GCP).

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Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly.

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