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As an AI Engineer at Aspora, you’ll start by shipping internal automation tools and workflows, and then extend the same AI capabilities into the product. This is a full-stack, production ownership role to build and scale intelligent systems at Aspora.
Job Responsibility:
Own the serving and runtime layer for all LLM-powered features, ensuring low latency, high reliability, and cost efficiency in production
Integrate LLM and agent capabilities into real product workflows, including tool calling, routing, guardrails, and safe failure modes
Build reliable, observable AI workflows across product, ops, and data systems, with strong foundations in retries, idempotency, fallbacks, and human-in-the-loop patterns
Design and operate retrieval and knowledge systems end-to-end, from ingestion and indexing to retrieval and response composition
Automate and harden operational processes, turning manual workflows into scalable, measurable pipelines
Own performance, reliability, and operational excellence across AI systems, measuring end-to-end latency, removing bottlenecks, and implementing pragmatic reliability patterns
Instrument and monitor AI systems in production, tracking quality regressions, drift, prompt failures, and retrieval issues with logs, metrics, and traces
Requirements:
At least 5 years of experience training, deploying, and scaling AI/ML models in production environments
You understand the pace and mindset of a startup and are excited to contribute to its growth and culture
Hands-on experience integrating third-party LLM APIs in production environments
Practical understanding of MLOps/LLMOps concerns: evaluation, monitoring, rollouts, incident response
Curiosity and drive to experiment with advanced AI techniques while staying grounded in production impact
Strong bias for measurable improvements: latency, cost, reliability
What we offer:
Competitive compensation and equity, aligned with experience, impact and market standards
Learning & development support, including professional development budgets and learning stipends
Wellness and team engagement programs to support work-life integration and collaboration