AI Software Engineer

Responsibilities

• 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.
• Architect and build Retrieval-Augmented Generation (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.
• 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.
• Integrate and optimize third-party speech and language services, developing custom connectors as needed; implement monitoring and logging systems and analyze key metrics (latency, throughput, accuracy) to recommend performance improvements.

Qualifications

• Minimum 5 years of experience in software development, with at least 2 years in the AI domain.
• 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.
• Strong understanding of vector embedding techniques and experience with vector stores such as Qdrant, FAISS, Annoy, or Pinecone.
• Proven ability to design and maintain end-to-end data pipelines (collection, cleaning, annotation, splitting).
• Minimum 1 year of production-level software development on Linux; proficient in Docker and Kubernetes and experience designing microservices architectures. Familiarity with CI/CD platforms (Jenkins, GitLab CI/CD, GitHub Actions) is a plus.
• Preferred: deep knowledge of vector database internals and operations; experience deploying multi-tenant online services with auto-scaling; familiarity with additional backend languages (Go, C++) or frontend frameworks (React, Vue); background integrating AI into financial, e-commerce, or telecom call-center platforms; publications or significant open-source contributions.