At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.
Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.
The Lead AI Engineer will build and lead Kpler's new AI Enablement crew, whose mission is to give every function in the company - from Engineering to People, IT, Customer Success, Legal, Finance, and the commercial teams - the tools, frameworks, and AI agents to work with AI at scale.
This is a hybrid leadership role: you set the technical direction and architecture for Kpler's internal AI tooling, stay hands-on on the most critical components, and manage a small crew (a Senior AI Engineer and an Engineer II to start), with the management scope expected to grow with the crew.
Build, lead, and grow the AI Enablement crew — technical direction, delivery, and light people management (1:1s, growth, feedback), evolving toward a fuller management scope as the crew expands.
Own the architecture of Kpler's internal AI tooling: agents and assistants, shared frameworks, knowledge bases, and the integrations that connect them to company systems.
Deliver function-tailored AI solutions in close partnership with functional champions across departments, from discovery and workflow design through production deployment and iteration.
Drive the AI software factory for engineering: codify engineering standards and architectural principles into rules, skills, and agents, and raise the level of AI-assisted development across all crews.
Establish and enforce security guardrails and responsible-AI practices for connecting AI systems to core company systems (access control, data privacy, human-in-the-loop where it matters).
Stay hands-on: design, build, and ship critical components of the platform yourself.
Define and track success metrics for internal AI - adoption and usage, workflows automated, time savings and ROI - and report progress to engineering and executive stakeholders.
Grow AI capability across the company: champions network, sharing sessions, documentation, and enablement.
Contribute to hiring and onboarding for the crew and to Kpler's broader engineering hiring.