Artificial Intelligence Engineer

Job Description

My name is Sachin Gupta, and I’m a recruiter with Reqroute Inc.
We are actively seeking talented professionals to support our client’s staffing needs and I wanted to reach out regarding an opportunity that may be of interest to you.
If you are open to exploring new opportunities, please feel free to contact me at +1 (408) 300-9060 or share your updated resume along with your availability for a discussion.
If you are not currently in the job market, I would appreciate it if you could refer someone in your network who might be a good fit.

Please reply with updated word formatted resume along with below details

FULL TIME ROLE

Onsite Monday – Thursday (Remote only on Friday)
Position Title: Sr. AI Developer/Architect
Location: 600 E. Las Colinas Blvd Irving TX 75039
Duration: Full Time
Position Type- Full Time
Exp Level- 10+Years

Skills: AI/ML Solutions, MS Stack, Azure, Azure Data Factory, MS Fabric (Microsoft Fabric), Python, MLOps, CI/CD, Leadership skills, Go-getter, Azure OpenAI Service, Azure Machine Learning (Azure ML), Azure Data Factory (ADF), Python, AI/ML Deployment & MLOps, Kubernetes/AKS, CI/CD Automation, Infrastructure as Code (Terraform / Bicep), LLM, Claude Code

Job Description
Microsoft Azure AI & Cloud Services
Azure OpenAI Service
Azure Machine Learning (Azure ML)
Microsoft Fabric
Azure Data Factory (ADF)
Python
AI/ML Deployment & MLOps
Kubernetes / AKS
GPU Workloads
Cloud Security & Governance
CI/CD Automation
Infrastructure as Code (Terraform / Bicep)

Skills Matrix
Number of year experience in Microsoft Azure AI & Cloud Services?
Number of year experience in OpenAI?
Number of year experience in Azure Machine Learning (Azure ML)?
Number of year experience in Microsoft Fabric?
Number of year experience in Azure Data Factory (ADF)?
Number of years experience in Azure Cloud?
Number of year experience in Python?
Number of year experience in AI/ML Deployment & MLOps?
Number of year experience in LLM?
Number of years experience in Claude Code?
Number of year experience in building and deploying machine learning or AI solutions in production?
Number of year experience in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)?
Number of year experience in LLM ecosystems (OpenAI APIs, Hugging Face, LangChain, vector databases)?
Number of year experience in data engineering fundamentals?
Ability to communicate complex technical ideas clearly and confidently?
Number of year experience in working directly with business stakeholders?
This role is ideal for a hands-on cloud AI engineer with deep expertise designing, deploying, securing, and optimizing enterprise AI platforms in Microsoft Azure environments.
The ideal candidate will possess strong experience with Azure AI services, cloud-native AI architecture, MLOps, scalable deployment patterns, and enterprise-grade security and governance.

Top Skills
Microsoft Azure AI & Cloud Services
Azure OpenAI Service
Azure Machine Learning (Azure ML)
Microsoft Fabric
Azure Data Factory (ADF)
Python
AI/ML Deployment & MLOps
Kubernetes / AKS
GPU Workloads
Cloud Security & Governance
CI/CD Automation
Infrastructure as Code (Terraform / Bicep)
Key Responsibilities
AI Platform Architecture & Deployment
Design, build, and deploy scalable AI/ML platforms in Microsoft Azure.
Implement enterprise AI solutions using Azure OpenAI, Azure ML, Azure AI Services, and Microsoft Fabric.
Architect end-to-end AI pipelines from data ingestion and preprocessing through model deployment, monitoring, and retraining.
Deploy GPU-intensive AI workloads using Azure Kubernetes Service (AKS), Azure VM Scale Sets, or containerized cloud environments.
Design highly available and fault-tolerant AI infrastructure supporting enterprise-scale workloads.
AI Engineering & Cloud Integration
Integrate AI solutions with Azure Data Factory, Azure Synapse, Microsoft Fabric, Databricks, and enterprise data platforms.
Build MLOps pipelines for automated training, testing, deployment, and model lifecycle management.
Implement CI/CD pipelines for AI solutions using Azure DevOps or GitHub Actions.
Develop APIs and scalable inference endpoints for AI applications and LLM-powered solutions.
Security, Governance & Optimization
Implement enterprise-grade security controls for AI workloads including RBAC, Managed Identities, Key Vault, Private Endpoints, and network isolation.
Ensure compliance with governance, data privacy, and responsible AI standards.
Optimize AI cloud infrastructure for performance, scalability, and cost efficiency.
Monitor AI workloads for latency, utilization, drift detection, and operational reliability.
Collaboration & Leadership
Partner with business stakeholders, architects, data engineers, and DevOps teams to deliver AI-driven business solutions.
Provide technical leadership on cloud AI architecture and deployment best practices.
Evaluate emerging AI cloud technologies and recommend scalable enterprise solutions.
Required Qualifications
5+ years of experience in Azure cloud engineering, AI deployment, or ML platform engineering.
Hands-on experience with Azure Machine Learning, Azure OpenAI, Azure AI Services, and Microsoft Fabric.
Strong experience deploying AI/ML models into production cloud environments.
Experience with Kubernetes, Docker, and scalable GPU-based deployments.
Strong understanding of cloud networking, identity management, and security architecture.
Experience implementing MLOps and CI/CD pipelines for AI systems.
Strong Python scripting and automation skills.
Experience with Infrastructure as Code tools such as Terraform, ARM Templates, or Bicep.

70% – Hands-On AI Development & Engineering
Design, build, and deploy scalable AI/ML solutions (predictive models, generative AI, NLP, optimization, automation)
Architect production-ready pipelines from data ingestion through model monitoring
Develop and fine-tune LLM-based applications (RAG architectures, prompt engineering, agents, copilots)
Write high-quality, production-grade code (Python required; additional languages a plus)
Implement MLOps best practices (CI/CD, model versioning, monitoring, drift detection)
Work across cloud platform (Azure) to deploy secure, enterprise-grade solutions
Ensure governance, security, explainability, and responsible AI principles are embedded in every solution
Optimize performance, scalability, and cost-efficiency of AI workloads
30% – Business Partnership & Solution Leadership
Translate ambiguous business problems into structured AI solution designs
Partner with business stakeholders (Finance, Operations, Sales, Marketing, IT) to identify high-value use cases
Clearly explain AI concepts, tradeoffs, and model outputs to non-technical audiences
Lead solution design workshops and whiteboarding sessions
Quantify expected ROI and define measurable success metrics
Influence prioritization of AI initiatives based on business value and feasibility
Mentor junior developers and help elevate AI literacy across the organization
What Success Looks Like
AI solutions deployed into production that generate measurable business impact
Reduced time-to-value from idea to implementation
Business leaders who trust and understand the AI solutions being delivered
Scalable architecture that enables repeatable AI delivery across functions
Required Qualifications
7+ years of software development experience
3+ years building and deploying machine learning or AI solutions in production
Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Experience with LLM ecosystems (OpenAI APIs, Hugging Face, LangChain, vector databases)
Solid understanding of data engineering fundamentals
Ability to communicate complex technical ideas clearly and confidently
Demonstrated experience working directly with business stakeholders