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23 hours ago
The role of AI Engineer Leader involves leading the development and integration of Python-based applications with large language models (LLMs). This entails architecting and implementing LLM pipelines, including prompt engineering, retrieval-augmented generation, fine-tuning, and evaluation.
Key responsibilities include designing scalable microservices and APIs for AI features, collaborating with machine learning operations teams to deploy and monitor AI models in production, and ensuring performance optimization, cost efficiency, and security in LLM workflows.
Additionally, the AI Engineer Leader will guide the team on Python best practices, code reviews, and technical problem-solving, as well as stay updated on emerging AI/LLM advancements and propose adoption where beneficial.
Mandatory Skills- Strong proficiency in Python, including experience with FastAPI and Flask.
- Solid experience with LLM integration, including OpenAI API, Hugging Face Transformers, LangChain, and LlamaIndex.
- Understanding of RAG pipelines and vector databases like Pinecone, Weaviate, FAISS, and Milvus.
- Experience with prompt engineering & evaluation techniques, knowledge of MLOps tools (MLflow, Kubeflow, Langfuse) and deployment on AWS/GCP/Azure.
- Familiarity with containerization and orchestration (Docker, Kubernetes).
- Strong grasp of REST APIs, GraphQL, and microservices architecture, knowledge of model fine-tuning and performance optimization.
- Excellent leadership and mentoring abilities, strong problem-solving and analytical skills.
- Effective communication with technical and non-technical stakeholders.
- Ability to work in a fast-paced, evolving AI environment.
- Experience with agentic AI or Model Context Protocol (MCP), background in data pipelines (ETL, streaming data).
- Exposure to AI security & compliance practices, prior work in scalable enterprise AI products.
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