About Us
We are a small team of researchers and engineers focused on pushing the frontier of what agents are capable of. We believe the next leap in agent performance will come not from bigger general models, but from specialization and continual learning: agents that get better at their specific job the more they do it. We build the systems that make this possible, turning real-world usage into lasting improvement.
Summary
We are looking for a senior Applied AI Engineer to work directly with our most important customers. You will embed with their engineering teams, understand their problems, and build specialized agents that keep improving the more they are used. This includes designing evaluations, training custom models, and deploying them at scale. You will be the technical lead on each engagement, from first conversation to production. You will also help shape how we work with customers.
Responsibilities
Lead technical discovery with customers to understand their workflows, constraints, and success criteria.
Build proofs of concept and production systems inside customer codebases and infrastructure.
Co-design evaluations and reward signals with customers that measure what matters for their business.
Advise on model and training strategy, and run training with customer data alongside our research team.
Build and deploy agents, tool integrations, and applications on top of customer-specific models.
Set up feedback loops in customer deployments so their agents keep improving over time.
Set up and tune model deployments for latency, throughput, and cost, including in customer VPCs.
Own the technical relationship through production launch and beyond.
Find repeatable patterns across customers. Turn them into product features, tools, and documentation with our product and research teams.
Communicate clearly with everyone from individual engineers to executives.
Qualifications
Software engineering experience that includes a customer-facing technical role such as Forward Deployed Engineer, Solutions Architect, or Applied ML Engineer. Former technical founders are encouraged to apply.
A track record of building production software with customers, not just advising them.
Strong Python skills and experience writing and debugging production code.
Production experience with LLMs, including agents, evaluations, and deployment at scale.
Working knowledge of how models are post-trained, with hands-on RL experience a strong plus.
Experience with cloud platforms (AWS, GCP, or Azure), Kubernetes, and GPU-based deployments.
Excellent communication skills. You can run a discovery call, present to a VP, and debug a production issue on the same day.
Willingness to travel and spend time on-site with customers.
Nice to Have
Experience with inference engines such as vLLM, SGLang, or TensorRT-LLM.
Experience training models or agents with reinforcement learning.
Experience working in regulated or security-sensitive environments, such as finance, healthcare, or the public sector.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Noeri develops AI-powered solutions for enterprise applications.