Lead Engineer - AI Enablement

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.

Your mission is to

• 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.

This could be a match if you have

Essential:

• 8+ years of software engineering experience, including designing and operating production systems end-to-end.
• Strong programming skills in Python and/or Golang (other JVM languages considered).
• Practical understanding of security, access control, and data-privacy constraints relating to AI systems.
• Experience leading engineering projects as a tech lead, lead engineer, or engineering manager of a small team.
• Hands-on experience shipping LLM-powered products, agents, or AI tooling to production (not just prototypes).
• Integration-heavy engineering background: connecting products to third-party SaaS systems and internal data via APIs.
• Strong stakeholder management with non-technical audiences; able to turn a business workflow into a deployable system.
• Experience with systems integration across commercial SaaS platforms and internal services.
• Exposure to Cloud environments (AWS preferred), CI/CD, and observability for production systems.

Desirable:

• Experience building internal tooling, platform, or enablement teams (DevEx, internal products).
• Familiarity with agent frameworks, MCP-style tool interfaces, and multi-agent systems.
• Experience with LLM evaluation, observability, and cost management of AI workloads.
• Experience introducing AI-assisted development practices to engineering organisations.
• Scale-up environment experience; comfort with ambiguity and building a function from scratch.