Senior AI Engineer

Job description

Senior AI Engineer Are you an experienced Senior AI Engineer looking for a new Role? Do you enjoy being part of a successful team? Responsibilities, Authorities, and Accountabilities 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. These teams typically include AI Engineers, Data Scientists, Software Engineers, Product Managers, Architects, Domain Experts, and business stakeholders, working in partnership with Baker Hughes business units to deliver measurable business value. In this role, you will: • 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. Required 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. Desired Characteristics Technical Expertise • 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. Domain Knowledge • Demonstrated knowledge of one or more industry sectors where Baker Hughes operates. • Demonstrated ability to identify, quantify, and deliver customer and business value through AI-enabled solutions. • Understanding of operational, engineering, commercial, or enterprise