AI / ML Engineer

JobDiva, Inc.; Plano (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

JobDiva, Inc. is seeking an AI ML Engineer to design, develop, and deploy Generative AI applications focusing on RAG and agentic workflows, utilizing the Azure stack and Langchain.

The role emphasizes building scalable enterprise AI solutions that integrate data from Azure Databricks, documents, and APIs. You will implement LLMs with prompt engineering, optimize vector databases for agent use, and collaborate with data engineers to productionize AI features while focusing on performance,

Qualifications

• 2+ years of experience in AI/ML Engineering, Data Science, or related field.
• Experience with Azure Databricks or similar relational databases.
• Strong hands-on experience with Python, Git, Langchain; RAG architectures and vector search concepts.
• Experience with Azure AI ecosystem, including Azure OpenAI models and Azure AI Search.
• Understanding of AI ML concepts, LLMs, vector databases, RAG, agents.

Responsibilities

• Design and build agentic applications using Langchain or similar, integrating enterprise data sources (Azure Databricks, documents, APIs).
• Build and optimize RAG vector databases for use by agents using tools like Azure AI Search, or similar.
• Integrate LLMs (Azure OpenAI, GPT models) into enterprise applications with proper prompt engineering and optimization.
• Implement evaluation, monitoring, and guardrails for AI systems (accuracy, bias, hallucination control).
• Collaborate with data engineers and application teams to integrate AI solutions into production systems.
• Optimize application performance, latency, and cost for large-scale deployments.
• Communicate insights clearly to both technical and non-technical stakeholders.

Skills

Python

LLM

RAG

APIs

Microservices

Communication

Tools

Azure Databricks

Langchain

Azure OpenAI

Azure AI Search

Git/GitHub

Job description

Job Summary:

We are seeking an AI ML Engineer to design, develop, and deploy Generative AI applications, with a focus on Retrieval-Augmented Generation (RAG) and agentic workflows. The ideal candidate will have hands-on experience building applications using LLMs, vector databases, and agent harnesses, along with experience in Azure stack. This role involves developing scalable, production-grade AI solutions that integrate enterprise data with advanced reasoning and automation capabilities.

Responsibilities:

• Design and build agentic applications using Langchain or similar, integrating enterprise data sources (Azure Databricks, documents, APIs).


• Build and optimize RAG vector databases for use by agents using tools like Azure AI Search, or similar.


• Integrate LLMs (Azure OpenAI, GPT models) into enterprise applications with proper prompt engineering and optimization.


• Implement evaluation, monitoring, and guardrails for AI systems (accuracy, bias, hallucination control).


• Collaborate with data engineers and application teams to integrate AI solutions into production systems.


• Optimize application performance, latency, and cost for large-scale deployments.


• Communicate insights clearly to both technical and non-technical stakeholders.

Minimum Qualifications:

• 2+ years of experience in AI/ML Engineering, Data Science, or related field.


• Experience using data from Azure Databricks or similar relational databases.


• Strong hands-on experience with Python (core development language), Git, Github; LLM frameworks especially Langchain; RAG architectures and vector search concepts.


• Experience with Azure AI ecosystem, including Azure OpenAI models and Azure AI Search.


• Understanding of AI ML concepts, LLMs, vector databases, RAG, agents.


• Familiarity with APIs, microservices, MCP and scalable system design.


• Strong communication skills.

External Skills And Expertise:

• RAG.


• Azure.


• AI.


• ML.


• LLM.