Proficiency with creating CI/CD pipelines and stages with Harness using YAML templates. Kong plugin development using Lua or Go. Experience with Package Managers like LuaRocks. Experience with containerization (Docker), and orchestration tools (Kubernetes). Experience with cloud platforms such as AWS, Google Cloud, or Azure. Familiarity with monitoring and logging tools like Datadog and OpenTelemetry.
AI Engineer
Location
United States
Posted
4 days ago
Salary
0
Seniority
Mid Level
No structured requirement data.
Job Description
AI Engineer
Texas State Library and Archives Commision
Role Description - 6-8 years of hands-on experience with Generative AI, AI, ML, and Data Science technologies. - Extensive hands-on experience in implementing end-to-end projects utilizing Generative AI. - Experience in building production-grade solutions utilizing Generative AI as well as AI and ML components. - Extensive hands-on experience in building Generative AI applications using methodologies such as: - RAG - Prompt engineering - Embedding - Fine-tuning - Experience in working with structured as well as unstructured data for building RAG-based solutions. - Experience with AI, ML search, and data services within the GCP ecosystem such as: - GCP Vertex AI - Vertex AI Vector Search - Gemini - Cloud Run - Cloud SQL - Experience with agent frameworks such as: - Google ADK - Langgraph - CrewAI - Hands-on experience in working with cloud AI services: - GCP Vertex AI - Azure AI - AWS Bedrock - Extensive experience in Python programming languages along with popular frameworks such as: - Flask - FastAPI - Experience with AIML, deep learning, TensorFlow, Python, and NLP. - Excellent understanding of Generative AI related concepts, methodologies, and techniques. Qualifications - Bachelor's degree in computer science or related field. - 5 years AIML experience including 2 years in GenAI projects. - Proficiency with Azure AI services and Python. - Experience with agent-based frameworks such as LangChain and LangGraph is highly desirable. - Solid understanding of API integration, test automation, and software engineering principles. - Good teamwork and communication skills. Requirements - Mandatory Skills: - MLOPS - GenAI - LLMOps - Machine Learning - AIOPS
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