We’re hiring an Applied AI Engineer to build the next generation of AI copilots inside Clueso. This role is about turning fast-moving LLM and vLLM capabilities into reliable, production-grade systems. You’ll work on agents that understand context, reason over complex inputs, and assist users inside real workflows not demos, not prototypes. We care far more about how you think than any specific framework. If you’re genuinely sharp, curious, and have spent real time working with contemporary AI systems, you’ll do outstanding here.

What you’ll work on
Building AI copilots that operate inside real product workflows
Designing agent architectures that combine LLMs, vLLMs, and deterministic systems
Translating fuzzy user intent into structured, reliable actions
Evaluating current models as they ship—and rethinking pipelines when capabilities change
Debugging and improving AI systems based on real user behavior, not benchmarks
Working closely with product and engineering to ship AI features end-to-end

This is not a research role. It’s applied, hands-on, and deeply tied to shipping.





What we’re looking for
2+ years working with modern AI systems, LLMs, or applied machine learning.
Exceptionally strong problem-solving ability and technical judgment
Prior experience working with LLMs or vLLMs in non-trivial systems
Comfort operating in ambiguous problem spaces with incomplete information
Ability to reason about tradeoffs between AI-driven and deterministic approaches
Strong software engineering fundamentals (you write clean, debuggable code)

We don’t care where you learned this—startup, big tech, research lab, or self-directed work. We do care that you’ve gone deep.

Nice to have (not required)
Experience building AI agents, copilots, or workflow automation tools
Familiarity with evaluation, reliability, and failure modes of LLM systems
Experience working with multimodal models (text, vision, audio, video)
Comfort iterating quickly as models and constraints

📌 Applied Ai Engineer Bengaluru
🏢 Clueso
📍 Bengaluru