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Senior Generative AI Engineer

Plano, TX, US • Posted 3 hours ago • Updated 3 hours ago

Full Time

On-site

Fitment

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Job Details

Skills

Software Engineering
MongoDB
NoSQL
Database Design
Data Modeling
Management
Cloud Computing
Semantic Search
Large Language Models (LLMs)
Language Models
Prompt Engineering
Optimization
Performance Analysis
LangChain
LlamaIndex
Regulatory Compliance
Machine Learning Operations (ML Ops)
Continuous Integration
Continuous Delivery
Lifecycle Management
Agile
Product Development
Microservices
Python
Workflow
Orchestration
Evaluation
Collaboration
Product Engineering
Use Cases
Semantics
Neo4j
Graph Databases
Vector Databases
Artificial Intelligence
Kubernetes
Docker
GitHub
Microsoft Azure
DevOps
Generative Artificial Intelligence (AI)

Software Engineering
MongoDB
NoSQL
Database Design
Data Modeling
Management
Cloud Computing
Semantic Search
Large Language Models (LLMs)
Language Models
Prompt Engineering
Optimization
Performance Analysis
LangChain
LlamaIndex
Regulatory Compliance
Machine Learning Operations (ML Ops)
Continuous Integration
Continuous Delivery
Lifecycle Management
Agile
Product Development
Microservices
Python
Workflow
Orchestration
Evaluation
Collaboration
Product Engineering
Use Cases
Semantics
Neo4j
Graph Databases
Vector Databases
Artificial Intelligence
Kubernetes
Docker
GitHub
Microsoft Azure
DevOps
Generative Artificial Intelligence (AI)

Summary

Required Qualifications

Core Software Engineering

8+ years of experience in software engineering with strong expertise in Python.
Hands-on experience designing and developing microservices-based architectures using FastAPI or similar Python frameworks.
Experience building scalable, secure, and production-grade APIs.

Cloud & Data Platforms

Strong experience with Microsoft Azure, including AI, data, and application services.
Expertise in MongoDB and NoSQL database design, optimization, and data modeling.
Experience deploying and managing cloud-native applications and containerized workloads.

Generative AI & Agentic Systems

Proven experience developing Generative AI solutions using modern LLM frameworks.
Hands-on experience building AI Agents, multi-agent systems, and autonomous workflows.
Strong understanding of Retrieval-Augmented Generation (RAG) architectures, including:
- Knowledge RAG
- Graph RAG
- Hybrid retrieval systems
- Context-aware retrieval pipelines
Experience designing enterprise knowledge bases, semantic search solutions, and context-building frameworks.

Large Language Models

Strong understanding of Large Language Models (LLMs) and Small Language Models (SLMs).
Experience with model selection, prompt engineering, grounding strategies, fine-tuning approaches, and inference optimization.
Familiarity with model performance, latency, cost optimization, and governance considerations.

AI Evaluation & Observability

Hands-on experience implementing Agentic Evaluation frameworks, including tools such as DeepEval.
Experience designing evaluation metrics for:
- Retrieval quality
- Hallucination detection
- Answer relevance
- Agent task completion
- Safety and reliability
Experience with AI observability and monitoring platforms, particularly Arize AI, for production monitoring, tracing, and model performance analysis.

Preferred Qualifications

Experience with vector databases and embedding models.
Familiarity with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar AI orchestration frameworks.
Experience building enterprise AI applications with governance, security, and compliance considerations.
Knowledge of MLOps/LLMOps practices, CI/CD pipelines, and model lifecycle management.
Experience working in Agile product development environments.

Key Responsibilities

Design and develop scalable AI-powered microservices and APIs using Python and FastAPI.
Build and maintain enterprise-grade RAG and Graph RAG solutions.
Develop intelligent agentic workflows that leverage organizational knowledge and business context.
Optimize knowledge retrieval, context orchestration, and response quality for AI applications.
Implement evaluation frameworks and monitoring solutions using DeepEval and Arize.
Deploy, monitor, and maintain AI applications on Azure.
Collaborate with product, engineering, and business teams to translate use cases into production-ready AI solutions.

Must have existing hands on experience

Azure AI Foundry
Azure OpenAI Service
Semantic Kernel
LangGraph
Neo4j or Graph Databases
Vector Databases (Azure AI Search, Pinecone, Weaviate, Qdrant)
Kubernetes and Docker
GitHub Actions / Azure DevOps

This version is targeted at a Senior Generative AI Engineer (7-10+ years of experience).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: RTL155990
Position Id: b001b8a913bb2779e0167cc78f984a31
Posted 3 hours ago

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