Full-Time AI Engineer

• BSc in Computer Science, Engineering, Mathematics, Physics, or related STEM field (MSc/PhD a plus).
• At least 3 years of experience building ML/AI solutions, including hands-on work with LLMs or Generative AI in production. Experience in financial services, credit risk, or banking is a plus.
• Skilled in Python, writing clean, modular, and tested code with async handling, dependency management, and testing practices. Familiarity with GenAI coding assistants (e.g., Cursor, Copilot) is a plus.
• Hands-on experience with LLM and Generative AI frameworks such as LangGraph, LangChain, or Pydantic AI for building workflows, RAG pipelines, and AI agents.
• Familiar with LLM fine-tuning methods such as Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).
• Proficient in ML/DL frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow for supervised, unsupervised, and time-series modeling.
• Familiar with MLOps and observability tools, including MLflow, Kubeflow, LangSmith, or Langfuse, for managing lifecycles and monitoring models end-to-end.
• Solid theoretical foundation in statistics, probability, optimization, and ML fundamentals such as bias/variance trade-offs, loss functions, and evaluation metrics.

• Experience with CI/CD and observability using Git-based automation (e.g., GitHub Actions, GitLab CI) and monitoring tools like Prometheus, Grafana, or OpenTelemetry.
• Exposure to data and feature pipelines with tools such as Airflow, Spark, or Kafka, including designing or contributing to workflows and feature stores.
• Familiarity with cloud-native development on AWS, Azure, or GCP, including containerized deployment with Docker/Kubernetes and basic infrastructure-as-code.
• Understanding of API and system architecture, including event-driven design and API exposure (REST/gRPC), with the ability to reason about latency, throughput, and scaling trade-offs.
• Awareness of security and compliance in ML, including responsible-AI practices, model governance, and secure deployment (e.g., GDPR, MLOps access control).

• Curious and inventive spirit; motivated to explore emerging techniques, experiment boldly, and translate ideas into working systems.
• Thrive in fast-moving, autonomous squads; action-oriented with a focus on continuous improvement.
• Excellent command of the English language (both verbal and written); clear communicator able to convey complex models into business value for non-technical stakeholders.
• Strong problem-solving and analytical thinking skills.
• Team player, self-motivated, and constantly seeking new knowledge.
• Growth mindset with strong alignment to EXUS values.
• Fulfilled military obligations (If applicable).

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