Technical Lead
1 week ago
Job Responsibilities
- Lead the development and integration of Python-based applications with LLMs (OpenAI, DeepSeek, Anthropic, LLaMA, etc.).
- Architect and implement LLM pipelines including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation.
- Design scalable microservices and APIs for AI features.
- Collaborate with MLOps teams to deploy and monitor AI models in production.
- Ensure performance optimization, cost efficiency, and security in LLM workflows.
- Guide the team on Python best practices, code reviews, and technical problem-solving.
- Stay updated on emerging AI/LLM advancements and propose adoption where beneficial.
Mandatory Skills
- Strong proficiency in Python (FastAPI, Flask).
- Solid experience with LLM integration (OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex).
- Understanding of RAG pipelines (vector databases like Pinecone, Weaviate, FAISS, 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.
Optional Skills
- 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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