Lead Generative AI Engineer

About the job

Lead Generative AI Specialist Are you a highly motivated, creative individual and passionate about sales and proposals? Would you like to be a part of successful team? Join our team! Are you passionate about building production‑grade AI systems that deliver real business value? Do you enjoy designing scalable platforms, deploying large language models, and operating AI services reliably in enterprise environments? Join our Digital Technology Team and help power the next generation of AI‑driven energy solutions. Our team develops industry‑leading products and services that optimize energy production and processing. In this role, you will focus on hands‑on generative AI engineering, working across model integration, AI platforms, and MLOps to operationalize large‑scale AI solutions that are secure, scalable, and performant.

Partner with the best As a Generative AI Specialist, you will be embedded in cross‑functional delivery teams, building, deploying, and operating generative AI services in a commercial and industrial context. You will work end‑to‑end across the AI lifecycle—from model onboarding and fine‑tuning to inference optimization, monitoring, and continuous improvement. As a Lead Generative AI Specialist, you will be responsible for:

- Engineering and deploying production‑ready generative AI solutions, including LLMs, VLMs, and multimodal models, with a strong emphasis on inference, scalability, and reliability.

- Designing and operating LLM Ops pipelines, including model versioning, fine‑tuning, evaluation, deployment, rollback, and lifecycle management.

- Building and maintaining AI platforms and services that support prompt management, embeddings, vector search, retrieval‑augmented generation (RAG), and tool‑calling workflows.

- Integrating generative AI capabilities into enterprise applications using APIs, microservices, and event‑driven architectures.

- Implementing MLOps best practices, including CI/CD for models, automated testing, performance benchmarking, observability, logging, and cost monitoring.

- Optimizing model performance across latency, throughput, accuracy, and cost using techniques such as quantization, catching, batching, and model routing.

- Collaborating with cloud, data, security, and product teams to ensure solutions meet enterprise standards for security, governance, and responsible AI.

- Producing clear technical documentation and operational runbooks and communicating delivery status and business value to stakeholders.

- Mentoring engineers and contributing to reusable frameworks, standards, and platform capabilities.

Fuel Your Passion To be successful in this role, you will have:

- A master’s degree in computer science, AI, Machine Learning, or a related field, or equivalent hands‑on industry experience.

- PhD is a plus, but strong delivery experience is preferred.

- Proven experience deploying and operating generative AI models in production, rather than only research or experimentation.

- Strong proficiency in Python, with practical experience using PyTorch, TensorFlow, Hugging Face, and transformer‑based architectures.

- Experience with AI platform and MLOps tooling, such as model registries, experiment tracking, orchestration, CI/CD pipelines, and monitoring solutions.

- Solid understanding of cloud‑native architectures, containers, and scalable inference patterns (e.g., Kubernetes‑based deployments).

- Hands‑on experience with RAG systems, vector databases, embeddings, prompt optimization, and evaluation frameworks.

- Strong software engineering discipline, including testing, code reviews, documentation, and production support.

- Excellent problem‑solving, collaboration, and communication skills, with the ability to work effectively across engineering and business teams.

- A delivery‑focused mindset, comfortable-owning systems in production and continuously improving them.  Work in a way that works for you We recognize that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too.

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

Working with us Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work. We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other.

Working for you   Our inventions have revolutionized energy for over a century. But to keep going forward tomorrow, we know we have to push the boundaries today. We prioritize rewarding those who embrace change with a package that reflects how much we value their input. Join us, and you can expect. 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

The Baker Hughes internal title for this role is: Lead Engineer, Mathematics & Data Science, Disciplinary Engineering and Science