Innovative Artificial Intelligence Solutions Specialist

We are seeking a skilled Artificial Intelligence Engineer to join our team in developing cutting-edge AI-powered solutions. As an integral member of our squad, you will be responsible for designing and implementing innovative AI models that drive business value.

The ideal candidate will possess a strong background in machine learning and AI, with hands-on experience in building and deploying production-grade AI systems. You should be proficient in programming languages such as Python and have a solid understanding of data structures and algorithms.

Experience with LLMs, Generative AI, and PyTorch is a plus. Additionally, knowledge of MLOps, model governance, and secure deployment practices would be beneficial.

In this role, you will work closely with cross-functional teams to design, develop, and deploy AI-powered features that drive real-world impact. You will be responsible for identifying opportunities to improve AI model performance, developing strategies to overcome technical challenges, and collaborating with stakeholders to ensure successful project outcomes.

• 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.

• 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 our values.
• Fulfilled military obligations (If applicable).

• Fully remote work setup
• Competitive salary
• Inclusive work environment & Well-being Program
• A clear induction program & a mentoring buddy to help you
• Private health insurance allowance
• Unlimited time off