AI Engineer
Role Description
As an AI Engineer, you will design, develop, and deploy Artificial Intelligence and Machine Learning solutions that solve real business problems. You will work on the full lifecycle of AI/ML solutions – from data exploration and model development to deployment, monitoring, and continuous improvement.
You will collaborate closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to translate requirements into scalable, production-ready AI systems, applying best practices in MLOps and responsible AI.
Key Responsabilities
- Design, develop, train, and validate machine learning and deep learning models to solve business problems.
- Build and maintain data pipelines for training, testing, and inference.
- Deploy AI/ML models into production environments, ensuring scalability, reliability, and performance.
- Collaborate with data scientists, software engineers, and business stakeholders to define requirements and translate them into technical solutions.
- Implement MLOps practices, including model versioning, CI/CD for ML, monitoring, and retraining pipelines.
- Evaluate and fine-tune pre-trained models (including LLMs) for specific use cases.
- Monitor model performance in production and implement improvements based on feedback and new data.
- Ensure AI solutions comply with data privacy, security, and ethical AI guidelines.
- Document technical solutions, architecture decisions, and processes.
- Stay up to date with the latest developments in AI/ML research and tools, proposing their adoption when relevant.
Job Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
- 4+ years of experience in AI/ML engineering or a related role.
- Solid understanding of machine learning, deep learning, and statistical modeling concepts.
- Proven experience taking models from prototype to production.
- Strong problem-solving skills and ability to work with ambiguous, real-world data.
- Good communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Fluency in English (written and spoken); [additional language] is a plus.
- Ability to work independently and as part of a distributed/remote team.
Main Tech Skills
- Programming Languages: Python (required); familiarity with R, Java, or Scala is a plus.
- ML/DL Frameworks: TensorFlow, PyTorch, Keras, scikit-learn.
- LLM & NLP: Hugging Face Transformers, LangChain, OpenAI/Anthropic APIs, prompt engineering, RAG architectures.
- MLOps Tools: MLflow, Kubeflow, DVC, Airflow.
- Cloud Platforms: AWS (SageMaker), Azure (Azure ML), or GCP (Vertex AI).
- Data Engineering: SQL, Spark, Pandas, NumPy.
- Containerization & Orchestration: Docker, Kubernetes.
- Vector Databases: Pinecone, Weaviate, FAISS, Chroma.
- Version Control & CI/CD: Git, GitHub Actions / GitLab CI / Jenkins.
- APIs & Microservices: REST/GraphQL API development, FastAPI, Flask.
Be Bold · Work Smart · Change Tomorrow
We started this company with a simple observation: most organizations don’t struggle because they lack technology — they struggle because solutions are too complex, disconnected from reality, or hard to sustain over time. Data and AI can create enormous value. But only when they are designed with clear intent, solid foundations, and a realistic understanding of how organizations actually operate. We’re a young, fast-growing company with plenty of opportunities to learn, evolve, and build something meaningful together.