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Role overview
Job description
Design, build, and operate AI systems for internal functions — agents, assistants, and automations — owning them end-to-end from design through production operation.
Build the shared foundations of the crew's platform: frameworks, knowledge-base pipelines, evaluation tooling, and reusable integrations with company systems.
Work directly with functional champions to understand their workflows, identify high-leverage automation opportunities, and turn them into deployed solutions.
Implement security guardrails and responsible-AI practices in everything shipped: access control, data privacy, auditability, and human-in-the-loop where it matters.
Make systems measurable: instrument adoption, quality, cost, and time savings, and use the data to iterate.
Keep owned systems reliable, observable, and maintainable - including production incident response and RCA.
Contribute to the AI software factory for engineering: rules, skills, and agents that codify Kpler's engineering standards, and AI-assisted development practices across crews.
Provide clarity through documentation, proposals, and runbooks; share knowledge across the crew and company.
Mentor other engineers in the crew and contribute to hiring and onboarding.
Experience & Background
Essential:
5+ years of software engineering experience building and operating production systems end-to-end.
Hands-on experience shipping LLM-powered features, agents, or AI tooling to production (not just prototypes).
Strong integration experience: third-party SaaS APIs, internal services, data pipelines.
Solid grounding in system design, APIs, databases, and application architecture.
Experience working directly with non-technical stakeholders to shape and deliver solutions.
Practical understanding of security and data-privacy constraints around AI systems.
Strong programming in Python and/or TypeScript.
LLM application engineering: model APIs, agent frameworks, prompt/context engineering, RAG and knowledge bases.
API design and systems integration across multiple SaaS platforms and internal systems.
Cloud environments (AWS preferred), CI/CD, containerisation.
Desirable:
Experience with agent frameworks, MCP-style tool interfaces, or multi-agent systems.
Experience with RAG/knowledge-base systems and LLM evaluation/observability tooling.
Experience building internal tools, platform tooling, or developer-experience products.
Cost optimization of LLM workloads.
Full-stack experience for user-facing internal tooling.
We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us? We make things happen We act decisively and with purpose, going the extra mile. We build together We foster relationships and develop creative solutions to address market challenges. We are here to help We are accessible and supportive to colleagues and clients with a friendly approach. Our People Pledge Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team. Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer. By applying, I confirm that I have read and accept the Staff Privacy Notice
About this listing
- Source: Kpler's official careers site · still listed there on 12 Nov 2026
- Posted 25 Aug 2026
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What they are looking for
Skills & requirements
Qualification
Hands-on experience shipping LLM-powered features, agents, or AI tooling to production (not just prototypes); LLM application engineering: model APIs, agent frameworks, prompt/context engineering, RAG and knowledge bases; Experience with RAG/knowledge-base systems and LLM evaluation/observability tooling; Cost optimization of LLM workloads
Department · Engineering
Hiring company
Kpler
Unlock global trade intelligence with Kpler’s real-time data on 40+ commodities, power markets, and maritime logistics, trusted by 10,000+ organisations.
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