Applied AI Engineer
Confirmed on the employer's own hiring board on Sep 27, 2026. First seen by Alion on Sep 16, 2026.
About the role
As an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production. This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real-world usage. Sounds great - what will I do? Build and ship AI features end-to-end (model, system,user experience) Design and iterate on prompts, tools, memory, and agent workflows Turn raw model outputs into structured, reliable, and predictable behaviors Debug issues across the full stack (model, orchestration, infra, UX) Optimize for latency, cost, and production reliability Develop lightweight evaluation frameworks to measure real-world performance Work closely with product and engineering to translate ambiguous problems into working systems
What you'll bring
Tech Stack Python PyTorch / JAX LLMs (OpenAI-style APIs, LLaMA, Qwen, etc.) Inference / serving (e.g. vLLM) Vector DB Ideal Experience Strong foundation in machine learning and modern neural network architectures. Hands-on experience with training, fine-tuning, or deploying ML models Ability to write clean, production-quality code Comfort working across abstraction layers (model, infra, product) Strong problem-solving skills in ambiguous, fast-moving environments Bias toward shipping, iteration, and continuous improvement