Senior AI Engineer

Role Description

As a Senior AI Engineer, you will be part of a multidisciplinary AI delivery team focused on designing, developing, deploying, and scaling AI-powered products and solutions. You will work on commercially facing projects involving Large Language Models (LLMs), Generative AI, machine learning systems, intelligent agents, and enterprise AI platforms.

• Work closely with customers and stakeholders to capture AI, automation, and business requirements and translate them into scalable technical solutions.
• Design, develop, evaluate, and deploy AI-powered applications using Generative AI, LLMs, agentic frameworks, machine learning models, and supporting services.
• Develop, validate, and optimize AI solutions to address customer needs and business opportunities while balancing quality, accuracy, performance, cost, and risk.
• Collaborate with software engineers and architects to translate AI prototypes into secure, scalable, and commercially viable products and services.
• Lead the development and deployment of production-grade AI solutions including Retrieval Augmented Generation (RAG), AI agents, prompt engineering, model orchestration, and model fine-tuning approaches.
• Work with Data Engineers and Platform teams to ensure data quality, governance, accessibility, and readiness for AI workloads.
• Define and execute experimentation strategies, benchmarking approaches, evaluation frameworks, and model performance monitoring processes.
• Monitor AI systems for quality, bias, safety, compliance, security, reliability, and continued business relevance.
• Generate technical documentation, design artifacts, reusable frameworks, and implementation guidance to support knowledge sharing and operational excellence.
• Communicate technical approaches, findings, risks, recommendations, and outcomes to both technical and non-technical stakeholders.
• Mentor junior AI Engineers and contribute to the growth of Baker Hughes' AI engineering capabilities, standards, and best practices.
• Contribute to AI platform evolution, architecture reviews, governance processes, and engineering standards across the organization.

Qualifications

• Bachelor's degree in computer science, Computer Engineering, Artificial Intelligence, Data Science, or other STEM discipline.
• Minimum of 6 years of professional experience in software engineering, machine learning, data science, AI engineering, or related technical fields.
• Demonstrated experience designing, developing, and deploying production-grade AI or machine learning solutions.
• Hands-on experience with Python and modern software engineering practices including source control, testing, CI/CD, and cloud-native development.

Requirements

• Demonstrated expertise in designing and delivering AI-powered applications and services.
• Strong understanding of Generative AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), prompt engineering, and agentic AI patterns.
• Experience integrating foundation models through platforms such as AWS Bedrock, Azure OpenAI, Google Vertex AI, or equivalent services.
• Demonstrated experience evaluating, fine-tuning, adapting, and operationalizing AI models for enterprise use cases.
• Experience working with vector databases, semantic search technologies, knowledge retrieval systems, and AI orchestration frameworks.
• Demonstrated understanding of responsible AI principles, model evaluation techniques, AI security considerations, and governance frameworks.
• Experience developing scalable cloud-based AI solutions and supporting MLOps/LLMOps practices.
• Demonstrated experience with software engineering and best practices, including microservices, testing, observability, and deployment automation.

Benefits

• Contemporary work-life balance policies and wellbeing activities.
• Comprehensive private medical care options.
• Safety net of life insurance and disability programs.
• Tailored financial programs.
• Additional elected or voluntary benefits.