Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Grapevine, TX, United States
Posted
19 hours ago
DockerFastAPIFlaskAWSMLOpsMLflowAirflowAzureGitGoogle CloudKafkaKubernetesLLMPython
Job Description
Hi,
Our client is looking for an Python Developer with AI exp in Southlake, TX, below is the detailed requirement.
Job positing Title: Python Developer with AI
Location: Southlake, TX
Job description:
Our client is looking for an Python Developer with AI exp in Southlake, TX, below is the detailed requirement.
Job positing Title: Python Developer with AI
Location: Southlake, TX
Job description:
5+ years of professional software development experience, with strong, current Python expertise.
Demonstrable experience delivering at least one AI/ML or LLM-powered system to production and supporting it through its life cycle.
Practical familiarity with the AI Development Life Cycle (AIDLC): data handling, experimentation, evaluation, deployment, and monitoring.
Hands-on experience with LLM application development — prompt engineering, RAG, and integrating APIs such as those from major model providers.
Proficiency designing and consuming RESTful APIs and building scalable backend services.
Working knowledge with cloud platforms (AWS, Google Cloud Platform, or Azure) and containerization (Docker).
Solid grounding with version control (Git) and CI/CD workflows.
Strong communication skills and the ability to work across engineering, data, and product teams.
Experience with agentic frameworks and orchestration (e.g., LangChain, LangGraph, LlamaIndex, or multi-agent frameworks).
Familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector, FAISS) and embedding-based retrieval.
Exposure to MLOps/LLMOps tooling — MLflow, Weights & Biases, model registries, and feature stores.
Experience with Kubernetes and infrastructure-as-code.
Understanding of model evaluation, responsible AI, safety guardrails, and observability for LLM systems.
Background with data pipelines and streaming (e.g., Kafka, Spark, or Airflow).
Python · FastAPI / Flask · LLM & Agentic frameworks · Vector databases · Docker · CI/CD · Cloud (AWS / Google Cloud Platform / Azure) · MLOps/LLMOps tooling
Demonstrable experience delivering at least one AI/ML or LLM-powered system to production and supporting it through its life cycle.
Practical familiarity with the AI Development Life Cycle (AIDLC): data handling, experimentation, evaluation, deployment, and monitoring.
Hands-on experience with LLM application development — prompt engineering, RAG, and integrating APIs such as those from major model providers.
Proficiency designing and consuming RESTful APIs and building scalable backend services.
Working knowledge with cloud platforms (AWS, Google Cloud Platform, or Azure) and containerization (Docker).
Solid grounding with version control (Git) and CI/CD workflows.
Strong communication skills and the ability to work across engineering, data, and product teams.
Experience with agentic frameworks and orchestration (e.g., LangChain, LangGraph, LlamaIndex, or multi-agent frameworks).
Familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector, FAISS) and embedding-based retrieval.
Exposure to MLOps/LLMOps tooling — MLflow, Weights & Biases, model registries, and feature stores.
Experience with Kubernetes and infrastructure-as-code.
Understanding of model evaluation, responsible AI, safety guardrails, and observability for LLM systems.
Background with data pipelines and streaming (e.g., Kafka, Spark, or Airflow).
Python · FastAPI / Flask · LLM & Agentic frameworks · Vector databases · Docker · CI/CD · Cloud (AWS / Google Cloud Platform / Azure) · MLOps/LLMOps tooling
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