Quick overview
SeniorityMid Senior
Work modeHybrid
LocationThornton, CO, United States
MicroservicesSQLMLOpsScikit-learnLLMPyTorchPythonTensorFlowVaultGenerative AIRESTAzurePostgreSQLMachine LearningPrompt EngineeringCI/CDRAG
Job description
Title: Applied AI Engineer
Location: Broomfield, CO (Need Local Only)
Work Arrangement: Hybrid
Duration: 6-Month Contract
Experience Range: 7-10 years
Interview: Video
Locals Only
Location: Broomfield, CO (Need Local Only)
Work Arrangement: Hybrid
Duration: 6-Month Contract
Experience Range: 7-10 years
Interview: Video
Locals Only
Share this job
Our client is seeking an Applied AI Engineer with 7–10 years of experience to design, build, and deploy enterprise-grade AI solutions, including generative AI and LLM-based applications, within a Microsoft Azure environment.
Our client is seeking an Applied AI Engineer with 7–10 years of experience to design, build, and deploy enterprise-grade AI solutions, including generative AI and LLM-based applications, within a Microsoft Azure environment.
Responsibilities & Qualifications
Design, build, evaluate, and deploy AI-enabled solutions for business-critical applications using Python, PyTorch, TensorFlow, and scikit-learn
Develop and deploy machine learning models with strong emphasis on model evaluation for accuracy, reliability, hallucination mitigation, latency, and cost optimization
Build generative AI and LLM-based applications, including AI agents and Retrieval-Augmented Generation (RAG) systems with prompt engineering expertise
Design secure agentic AI solutions that interact safely with enterprise systems, incorporating guardrails, validation, retries, approval workflows, and human oversight
Integrate AI solutions with enterprise APIs, databases (PostgreSQL), and Azure messaging systems (Service Bus, Event Hubs)
Collaborate with cloud and platform engineering teams to productionize AI solutions, implementing MLOps and LLMOps best practices
Translate operational problems into practical, enterprise-integrated AI solutions aligned with business objectives
Requirements
7–10 years of software engineering or data science experience with demonstrated expertise in Python and machine learning frameworks
Strong proficiency in generative AI, LLM applications, embeddings, vector databases, and agentic AI solutions
Hands-on experience with Microsoft Azure services: Azure OpenAI, Azure AI Services, Azure API Management, Azure Service Bus, Event Hubs, PostgreSQL, Entra ID, Key Vault, Monitor, and Application Insights
Advanced knowledge of machine learning operations (MLOps, LLMOps), CI/CD pipelines, REST APIs, and microservices architecture
Expert-level SQL and database design with PostgreSQL experience
Fluent English proficiency for technical communication and cross-team collaboration
Portfolio or proven track record demonstrating end-to-end AI solution delivery in enterprise environments
Design, build, evaluate, and deploy AI-enabled solutions for business-critical applications using Python, PyTorch, TensorFlow, and scikit-learn
Develop and deploy machine learning models with strong emphasis on model evaluation for accuracy, reliability, hallucination mitigation, latency, and cost optimization
Build generative AI and LLM-based applications, including AI agents and Retrieval-Augmented Generation (RAG) systems with prompt engineering expertise
Design secure agentic AI solutions that interact safely with enterprise systems, incorporating guardrails, validation, retries, approval workflows, and human oversight
Integrate AI solutions with enterprise APIs, databases (PostgreSQL), and Azure messaging systems (Service Bus, Event Hubs)
Collaborate with cloud and platform engineering teams to productionize AI solutions, implementing MLOps and LLMOps best practices
Translate operational problems into practical, enterprise-integrated AI solutions aligned with business objectives
Requirements
7–10 years of software engineering or data science experience with demonstrated expertise in Python and machine learning frameworks
Strong proficiency in generative AI, LLM applications, embeddings, vector databases, and agentic AI solutions
Hands-on experience with Microsoft Azure services: Azure OpenAI, Azure AI Services, Azure API Management, Azure Service Bus, Event Hubs, PostgreSQL, Entra ID, Key Vault, Monitor, and Application Insights
Advanced knowledge of machine learning operations (MLOps, LLMOps), CI/CD pipelines, REST APIs, and microservices architecture
Expert-level SQL and database design with PostgreSQL experience
Fluent English proficiency for technical communication and cross-team collaboration
Portfolio or proven track record demonstrating end-to-end AI solution delivery in enterprise environments
Thanks & Regards
Swati Patra
Technical Recruiter
Email:
Contact Number: +1
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