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Remote mid-level AI role with broad LLM requirements and metro appeal increases applicant competition.
Core AI engineering skills transfer across industries, but Baker Hughes domain knowledge preference raises sensitivity slightly.
Explicit 6-year minimum plus mandatory LLM, production, and MLOps skills create strict filters.
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Design, develop, deploy, and scale commercial AI-powered products and solutions involving Generative AI, LLMs, machine learning, and AI agents.
Collaborate with cross-functional teams and stakeholders to translate business and AI requirements into scalable, production-ready AI solutions, ensuring quality, performance, and security.
Lead AI solution development including RAG, prompt engineering, model orchestration and fine-tuning; oversee AI system monitoring, experimentation, and governance; mentor junior engineers.
Bachelor's degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, or related STEM field.
Minimum 6 years of professional experience in software engineering, machine learning, AI engineering, or related technical fields.
Proven experience designing, developing, and deploying production-grade AI or machine learning solutions.
Hands-on experience with Python and modern software engineering practices (source control, testing, CI/CD, cloud-native development).
Strong expertise in Generative AI, Large Language Models, Retrieval Augmented Generation, prompt engineering, and agentic AI frameworks.
Experience integrating foundation AI models via platforms like AWS Bedrock, Azure OpenAI, Google Vertex AI, and operationalizing enterprise AI solutions with MLOps/LLMOps.
Demonstrated ability to lead cross-functional AI technical initiatives, mentor engineers, and communicate technical concepts to varied stakeholders while driving AI strategy and standards.