AI Application Engineer NO C2C

We are seeking a highly skilled AI Development Engineer to design, build, and deploy advanced Claude AI-based, .NET-stack solutions that power next-generation products and internal platforms. This role is ideal for someone who thrives at the intersection of software engineering, AI application, and business outcomes. You will work closely with cross-functional teams to translate business needs into scalable, production-ready systems leveraging AI for coding.

The ideal candidate has at least six months of serious, hands‑on experience building with Claude and the passion to drive projects independently from concept to production. Some exposure to compliance requirements within financial services is preferred but not required.

• Develop Claude-based applications for real-world use cases on a .NET stack.
• Build scalable data pipelines and model‑serving infrastructure for high-performance AI systems.
• Collaborate with product, engineering, and research teams to define technical requirements and deliver end‑to‑end AI solutions.
• Implement and maintain MLOps workflows, including model versioning, monitoring, and continuous improvement.
• Conduct experiments, evaluate model performance, and apply state‑of‑the‑art techniques to improve accuracy and efficiency.
• Integrate AI models into production environments using APIs, microservices, or cloud‑native architectures.
• Stay current with emerging AI technologies, frameworks, and best practices.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering, software development, or applied machine learning.
• 6+ months of demonstrated, hands‑on experience building with Claude — this is a firm requirement.
• Strong proficiency in Python and ML frameworks such as Tensor Flow, PyTorch, or Scikit‑learn.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Solid understanding of data structures, algorithms, and distributed systems.
• Hands‑on experience with model deployment, inference optimization, and API development.
• Familiarity with NLP, computer vision, generative AI, or LLM fine‑tuning is a plus.

• Some exposure to compliance requirements within the asset management or hedge fund industry.
• Experience with vector databases, retrieval‑augmented generation (RAG), or LLM orchestration frameworks.
• Knowledge of MLOps tools such as MLflow, Kubeflow, Sage Maker, or Vertex AI.
• Background in reinforcement learning, generative modeling, or multimodal AI.
• Contributions to open‑source AI/ML projects.