Description
Senior AI Engineer responsible for building, tuning, and deploying production-grade Generative AI and LLM applications.
Responsibilities
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, including advanced techniques and prompt engineering strategies.
- Build, tune, and deploy LLM-based applications using platforms like Vertex AI and Hugging Face.
- Develop agentic framework use cases and integrate generative AI with enterprise systems via APIs and orchestration tools.
- Establish MLOps principles, model evaluation metrics, and CI/CD pipelines for automated testing and deployment.
- Manage containerized applications using OpenShift or Kubernetes in cloud-native environments.
Required Skills
- 10+ years of experience in Apps Development or Systems Analysis.
- Deep expertise in GenAI, Machine Learning, NLP, Neural Networks, and LLMs (Gemini, Claude, Llama, etc.).
- Strong proficiency in Python, including Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, LangChain, and LlamaIndex.
- Hands-on experience with vector databases (PG Vector, Pinecone, Mongo Atlas, Neo4j) and unstructured data processing.
- Proven track record of deploying GenAI models to production with robust MLOps practices.
- Experience with CI/CD tools: Jenkins, GitLab CI, Azure DevOps, or ArgoCD.
- Knowledge of Guardrails and methodologies for assessing GenAI performance and safety.
Preferred Skills
- Bachelor's degree in Computer Science, Engineering, or related field.
- Experience with knowledge graphs and high-throughput data processing architectures.