AI Software Engineer
1 week ago
Key Responsibilities
LLM Model Optimization
- Lead fine-tuning and optimization of large language models (LLMs) to improve accuracy and robustness in call-center scenarios.
- Design and implement conversation pipelines and plugin architectures using LangChain and LangGraph for efficient, scalable query and retrieval workflows.
Retrieval-Augmented Generation (RAG) & Knowledge-Based Construction
- Architect and build RAG workflows: set up vector stores, retrieval modules, and integrate them with LLMs to generate context-aware responses.
- Collect, clean, annotate, and preprocess datasets, design automated pipelines for ingestion and continuous knowledge base updates.
System Integration & Engineering
- Develop production-grade Python services on Linux, writing clean, maintainable, and scalable code.
- Containerize and orchestrate model services using Docker and Kubernetes; establish CI/CD pipelines for automated builds, tests, and deployments.
Performance Monitoring & Continuous Iteration
- Integrate and optimize third-party speech and language services, developing custom connectors as needed.
- Implement monitoring and logging systems; analyze key metrics (latency, throughput, accuracy) and recommend performance improvements.
Qualifications
Experience
- Minimum 5 years of experience in software development, with at least 2 years in the AI domain.
- Programming & Frameworks
- Expert in Python and at least one deep learning framework (TensorFlow, PyTorch, or JAX).
- Hands-on experience with LLM fine-tuning, prompt engineering, LangChain, and LangGraph.
Data & Algorithms
- Strong understanding of vector embedding techniques and experience with tools such as Qdrant, FAISS, Annoy, or Pinecone.
- Proven ability to design and maintain end-to-end data pipelines (collection, cleaning, annotation, splitting).
Systems & Deployment
- Minimum 1 year of production-level software development on Linux.
- Proficient in Docker and Kubernetes, with experience designing microservices architectures.
- Familiarity with CI/CD platforms (Jenkins, GitLab CI/CD, GitHub Actions) is a plus.
Preferred Qualifications
- Deep knowledge of vector database internals and operations (e.g., Qdrant, Milvus, Weaviate, Pinecone).
- Experience deploying multi-tenant online services with auto-scaling.
- Familiarity with an additional backend language (Go, C++) or frontend frameworks (React, Vue).
- Background in integrating AI into financial, e-commerce, or telecom call-center platforms.
- Publications in related fields or significant open-source contributions.
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