Senior AI Engineer

Technical Skills

1. Strong proficiency in Python + ML ecosystem (PyTorch, TensorFlow, scikit‑learn, Hugging Face, LangChain).

2. Proven experience deploying production-grade AI/ML systems, as reflected in organizational resumes (e.g., computer vision pipelines, real-time inference services).

3. Hands-on experience with LLMs, RAG architecture, vector databases (FAISS, Qdrant, Azure AI Search).

4. Solid understanding of software engineering fundamentals: API development, microservices, distributed systems.

5. Experience with Docker and Kubernetes, widely used in production deployments across internal candidates.

6. Proficiency with cloud platforms (GCP preferred; AWS/Azure also welcome).

7. Strong grasp of CI/CD, automated testing, model lifecycle management, and observability.

8. Familiarity with real-time processing (streaming, queues, event-driven architecture).

Soft Skills

1. Fast learner with ability to adopt new AI frameworks and technologies quickly.

2. Strong problem-solving mindset with practical approach to converting POC into production systems.

3. Clear communicator who can explain technical concepts to a variety of stakeholders.