AI Platform Engineer

The Role

AI Platform Engineers build the infrastructure that turns impressive AI demos into dependable production systems. You will work on retrieval, evaluation, agent orchestration, observability, data boundaries, and model-facing infrastructure for client products and internal delivery tooling.

The work sits between application engineering, data engineering, MLOps, and product judgment.

What You Will Do

• Design and implement retrieval-augmented systems with clear permission boundaries.
• Build evaluation suites for prompts, retrieval quality, model changes, and regressions.
• Create orchestration patterns for agentic workflows with human review.
• Instrument AI systems for cost, latency, quality, drift, and failure visibility.
• Help teams choose when to use hosted models, open-source models, fine-tuning, or simpler deterministic systems.
• Build internal tools that help Lukla engineers safely delegate more implementation work to agents.
• Document operating playbooks for production AI systems.

What We Are Looking For

• Strong backend or platform engineering experience.
• Practical experience with LLM APIs, embeddings, vector stores, RAG, evals, queues, and observability.
• Good instincts around security, PII, prompt injection, and data leakage.
• Comfort moving from prototype to production without overcomplicating the first version.
• Ability to explain AI system behavior to non-AI stakeholders.

Success Looks Like

AI features become measurable systems, not magic demos. Teams can change prompts, models, retrieval strategy, and workflows with confidence because the platform exposes quality, cost, and risk clearly.