The AI Engineer will create and implement advanced AI solutions powered by large language models and Generative AI technologies. This role emphasizes developing robust, ethical, and scalable AI systems for production use, working closely with data scientists, engineers, and business partners.
Responsibilities
- Design and implement Generative AI and machine learning systems using large language models and contemporary AI tools.
- Apply techniques such as fine-tuning LLMs, prompt engineering, retrieval-augmented generation, and model optimization.
- Deploy and oversee AI/ML pipelines and Generative AI applications in production on cloud platforms like Azure or GCP.
- Construct and maintain agentic AI systems using current orchestration and agent frameworks.
- Process large datasets to build data pipelines that support effective model training and evaluation.
- Build AI solutions using Python and up-to-date machine learning libraries.
- Manage deployment processes and infrastructure operations in Linux environments.
- Ensure secure handling and governance of sensitive information, including PII and PHI, in line with enterprise security and compliance policies.
- Optimize AI models and underlying infrastructure for performance, scalability, reliability, and cost-effectiveness.
- Work with cross-functional teams to integrate AI models into enterprise applications and live systems.
- Document model designs, experimental results, deployment workflows, and operational procedures.
- Remain updated on advancements in Generative AI, large language models, and AI engineering practices.
Requirements
- Bachelor’s degree in Engineering, Computer Science, AI/ML, Data Science, or another relevant technical discipline.
- Over 10 years of professional experience in software engineering, machine learning, or AI engineering.
- At least 3 years of direct experience with Generative AI technologies and large language models.
- Strong proficiency in Python programming.
- Demonstrated experience in fine-tuning, deploying, and optimizing large language models.
- Proven track record deploying Generative AI solutions into production settings.
- Hands-on experience operating in Linux-based environments.
- Familiarity with cloud platforms such as Microsoft Azure or Google Cloud Platform.
- Experience building and managing ML pipelines and deploying models using modern MLOps approaches.
- Experience managing and protecting sensitive data like PII and PHI according to regulatory and security standards.
Tech Stack
Python, Large Language Models (LLMs), Generative AI, Fine-tuning, Prompt Engineering, Retrieval-Augmented Generation (RAG), Model Optimization, Azure, GCP, MLOps, AI/ML Pipelines, Agentic AI Systems, Linux
Compensation
Not specified
Work Arrangement
Not specified
Team
Collaborative environment involving data scientists, software engineers, and business stakeholders to deliver enterprise AI solutions.
Additional Information
- Must securely manage sensitive data such as PII and PHI in accordance with enterprise security and regulatory requirements.
- Requires close collaboration with data scientists, software engineers, and business stakeholders.
- Must ensure AI systems are reliable, responsible, and capable of solving complex enterprise challenges.
Not specified
