Lead Python AI Solution Engineer
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ResponsibilitiesDesign and deliver production-ready AI and LLM applications in PythonDevelop and sustain RAG pipelines along with AI agent architecturesImplement and connect APIs that enable AI-driven capabilitiesDeploy and operate AI systems across cloud environmentsEnsure secure, scalable integration across platforms and servicesCollaborate with client Technical Leadership to set project direction and architectureEvaluate technical trade-offs with strong analytical judgment and recommend solutionsPrototype and prove AI concepts using the right frameworks and toolsSupport experimentation and model tracking throughout the development lifecycleTranslate business requirements into dependable technical implementationsRequirements5+ years of professional software engineering experience, including substantial hands-on delivery of production AI and LLM applicationsHigh proficiency with Python 3.11/3.12+ as your primary programming languageDeep experience with LLM application and agent frameworks such as LangChain, LlamaIndex, and PydanticAIWorking knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizersHands-on familiarity with Python project and dependency tooling such as uv, venv, and PoetrySolid command of code quality and development tools including Ruff, Pytest, and JupyterStrong background with machine learning libraries such as NumPy, pandas/Polars, and scikit-learnPractical understanding of deep learning frameworks such as PyTorch and TensorFlow/KerasProven track record implementing vector search and RAG infrastructure such as FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQLHands-on experience building AI APIs and deployment components with FastAPI, Pydantic, and UvicornDemonstrated skills in containerization and orchestration using Docker and KubernetesExperience working with data infrastructure technologies such as PostgreSQL, Redis, and Apache KafkaEnglish proficiency at B2 level (Upper-Intermediate) or higherNice to haveExperience applying TRL for LLM post-trainingKnowledge of DSPy for building programmatic LLM pipelinesFamiliarity with LiteLLM to unify access to multiple LLM APIsExperience with experiment tracking tools such as MLflow and Weights & BiasesPortfolio of AI application UI work using Streamlit, Gradio, or FastAPI with React/Next.js/Angular 19+
We offer
International projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn
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