Delta System & Software, Inc.
Generative AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Generative AI Engineer with 4–8 years of software engineering experience, including 1–2 years in AI/ML. Requires hands-on Python skills, LLM frameworks, and agentic frameworks. Contract length and pay rate unspecified; work location not provided.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 13, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Python #GCP (Google Cloud Platform) #Deployment #AI (Artificial Intelligence) #Cloud #Langchain #ML (Machine Learning) #DevOps #GIT
Role description
Core Skills & Experience
Must Haves
● 4–8 years of software engineering experience with at least 1–2 years in AI/ML or GenAI
systems in production
● Hands-on experience with Python only for AI/ML model integration.
● Experience with LLM frameworks (LangChain, LlamaIndex is a must
● Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI is a must
● Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment
practices.
Nice-to-Have
● Familiarity with Google Cloud Platform (GCP) — especially Vertex AI, Cloud Run, and
GKE.
● Experience building AI APIs, embeddings, vector search, and integrating them into
applications.
● Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with
OpenAI APIs.
● Exposure to multi-modal AI systems (text, image, or voice).
● Familiarity with Low-Code/No-Code tools (e.g., AppSheet) for workflow integration.
Core Skills & Experience
Must Haves
● 4–8 years of software engineering experience with at least 1–2 years in AI/ML or GenAI
systems in production
● Hands-on experience with Python only for AI/ML model integration.
● Experience with LLM frameworks (LangChain, LlamaIndex is a must
● Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI is a must
● Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment
practices.
Nice-to-Have
● Familiarity with Google Cloud Platform (GCP) — especially Vertex AI, Cloud Run, and
GKE.
● Experience building AI APIs, embeddings, vector search, and integrating them into
applications.
● Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with
OpenAI APIs.
● Exposure to multi-modal AI systems (text, image, or voice).
● Familiarity with Low-Code/No-Code tools (e.g., AppSheet) for workflow integration.
