Artificial Intelligence Engineer

Insight Global is looking for a AI Engineer for one of their premier Energy Trading clients in London, UK. The AI Engineer will join a vibrant team of Data Scientists and ML Engineers working with the Trading & Supply Capability Center (CC). He or she will be responsible for initiating, development and deployment of GenAI solutions/products in an agile fashion to meet demand across multiple business lines.

Key Characteristics include:

• Lead the technical direction of GenAI focused projects and initiatives
• Mentor junior AI engineers and help software engineers upskill on GenAI relevant techniques and tools
• Working within the Data Science and ML team to build and deploy GenAI solutions to production, using existing and emerging methods and technologies that could be effectively applied to use cases
• Build core infrastructure around feature engineering, model training, model deployment, ongoing monitoring tools, and much more.
• Building and define key evaluation systems and processes to ensure GenAI Tooling performs at a high standard
• Help guide and define strategic ambitions relevant to GenAI tooling and projects
• Work closely with Infrastructure, data engineering and DevOps teams to increase deployment velocity, including the process for deploying tools into production
• Work closely with Product Management to translate product requirements into robust, customer-agnostic machine learning architectures
• Keep abreast of new engineering practices, technologies and continuously improving our Agile practices and building and strengthening relationships and alliances in academia, tech teams and industry
• Contribute to community building initiatives like CoE, CoP.

Must Haves:

• Experience in designing, developing, deploying, and monitoring machine learning and GenAI solutions
• Experience working with data scientists and/or ML engineers and building auto-scaling ML systems
• Deep knowledge of LLM architectures and attention mechanisms – experienced with MoE, MHA, SWA, Flash Attention, GPT, LLaMA, DeepSeek, and reasoning-based models
• Experience in creating and maintaining RAG supported systems including PDF extraction, OCR, and varying chunking and embedding methodologies
• Inference optimisation experience – hands-on with high-performance inference frameworks such as vLLM, TensorRT, and related acceleration techniques
• Proven evaluation experience – successfully conducted assessments of RAG and agentic systems. Both on performance and compliance (harm, guardrails, etc)
• 4+ years of development competency across a variety of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka
• Background in Application development, deployment, and monitoring on Kubernetes
• Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates strong understanding of neural networks and LLMs; familiar with frameworks widely used in Hugging Face models, LLaMA, and similar architectures
• Expertise in fine-tuning methodologies – including data collection strategies for effective model adaptation (embeddings included)

Pluses:

• Commodity Trading Expertise – Short-term and physical trading across energy commodities (oil, gas, power, renewables, and related derivatives)
• Risk - Modelling & understanding of risk & risk management
• Commodity Modelling - Energy (power, gas, environmental products) and meteorology
• Data engineering skills using Azure/AWS/Google cloud native tools
• Good experience in Bash\Powershell Scripting and Linux Operating system and networking fundamentals
• Front end application development
• Active in various AI communities relevant to the newest technology and implementations patterns
• Master’s/PHD degree in any of the following: Engineering, statistics, machine learning, computational linguistics or relevant areas