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
