Job Description
JourneyTeam is seeking an experienced Senior Software Developer (AI Engineer) to join our Azure Practice. The ideal candidate will design, develop, and deploy AI and machine learning solutions using Azure's AI services while collaborating with cross-functional teams to deliver enterprise-grade solutions.
About JourneyTEAM:
At JourneyTeam, people are at the center of everything we do. Our purpose as a company is to help others effectively use technology to create a positive, lasting impact on the world. With 30 years of technology experience, we are 100% focused on delivering Microsoft business applications and technologies that empower organizations to reach new heights of business success. We deeply understand the transformative value of Microsoft solutions and are dedicated to helping our customers unlock their full potential. Our experienced team specializes in driving success across Dynamics 365, Microsoft 365, AI and Copilot, Azure, modern data solutions—all leveraging Microsoft’s comprehensive security platform.
Duties and Responsibilities:
- Design and implement AI/ML solutions using Azure AI services, including Azure Machine Learning, Cognitive Services, and Azure OpenAI Service.
- Develop and optimize machine learning models for production deployment on Azure infrastructure.
- Create end-to-end MLOps pipelines for model training, testing, and deployment.
- Integrate AI solutions with existing enterprise applications and data platforms.
- Design and implement containerized AI solutions using Kubernetes and Azure Kubernetes Service (AKS).
- Establish and maintain CI/CD pipelines for automated model deployment and testing.
- Implement version control best practices for both code and ML models.
- Provide technical leadership in AI solution architecture and best practices.
- Partner with clients to gather requirements and translate business needs into technical solutions.
- Mentor junior team members and contribute to building AI capabilities within the practice.
- Stay current with latest developments in Azure AI services and machine learning technologies.
Qualifications:
- Bachelor's degree in Computer Science, Data Science, or related field.
- 5+ years of software development experience.
- 3+ years of experience with machine learning and AI technologies.
- Strong proficiency in Python and its ML/AI frameworks (TensorFlow, PyTorch, scikit-learn).
- Extensive experience with Azure AI services and Azure Machine Learning.
- Microsoft Azure AI Engineer Associate certification (or willing to obtain within 3 months).
- Advanced experience with Git and version control workflows.
- Proven experience with Kubernetes and container orchestration.
- Strong background in CI/CD implementation and DevOps practices.
- Experience with MLOps practices and tools.
- Strong understanding of data structures, algorithms, and software design patterns.
- You embrace and live the JourneyTEAM Values below:
- A Caring Mindset
- Exceptional Performance
- Being OneTeam
- Making & Keeping Commitments
- Taking Ownership
- Effective Communication
- A Growth Mindset
Technical Skills:
Below, you'll find common languages, tools, platforms, and frameworks that you will regularly interact with and use on the job.
Programming & AI/ML
- Programming: Python, R, SQL, C#/.NET
- AI/ML Frameworks: TensorFlow, PyTorch, scikit-learn, Keras
- Azure Services: Azure Machine Learning, Cognitive Services, Azure OpenAI Service, Azure Databricks
- MLOps Tools: Azure DevOps, GitHub Actions, MLflow
- Development Tools: Docker, Visual Studio Code, Jupyter
Cloud & Infrastructure
- Cloud Platforms: Microsoft Azure (required), other cloud platforms a plus
- Container Orchestration:
- Kubernetes (AKS)
- Helm
- Container networking
- Kubernetes operators
- Service mesh implementations
Development & Version Control
Version Control:
- Advanced Git workflows
- Branch strategies (GitFlow, trunk-based development)
- Code review processes
- Monorepo management
- Git LFS for large files and models
CI/CD & DevOps
- Pipeline Tools:
- Azure DevOps
- GitHub Actions
- Jenkins
- ArgoCD
- Infrastructure as Code:
- Terraform
- Azure ARM templates
- Bicep
- Continuous Integration:
- Automated testing
- Code quality gates
- Security scanning
- Continuous Deployment:
- Blue-green deployments
- Canary releases
- A/B testing
- Rollback strategies
Preferred Skills (not required):
- Master's degree in Computer Science, AI, or related field.
- Experience with Azure OpenAI Service and large language models.
- Additional Azure certifications (Azure Solutions Architect, Azure Data Scientist).
- Experience with distributed computing and big data technologies.
- Contributing to open-source ML/AI projects.
- Experience in consulting or client-facing roles.
- Publication record in AI/ML conferences or journals.
Here at JourneyTEAM, we care about our employee’s growth. Here is what success looks like your first year:
30 Days:
- Complete setup for development environments, including Azure Machine Learning workspaces, Azure DevOps access, and Kubernetes clusters.
- Become familiar with JourneyTEAM’s current AI solutions, tools, and libraries, as well as key client use cases.
- Shadow senior AI engineers and project leads to understand project lifecycles, client requirements, and best practices.
- Join all relevant team meetings to observe cross-functional collaboration on active AI/ML projects.
- Assist on an AI/ML project to apply familiarity with Azure Machine Learning, Cognitive Services, and/or Azure OpenAI Service.
- Participate in client meetings as an observer to start understanding client expectations, technical requirements, and how JourneyTEAM solutions align with their needs.
6 months:
- Lead a mid-sized AI/ML project from design through deployment, overseeing all aspects of solution architecture, model training, and deployment in an enterprise Azure environment.
- Ensure that projects adhere to best practices in model optimization, code versioning, and container orchestration using Kubernetes and AKS.
- Fully leading multiple client meetings, gathering requirements and translating them into actionable technical solutions.
- Take full ownership of multiple AI projects, from scoping through deployment and maintenance, establishing JourneyTEAM as a reliable partner for Azure-based AI solutions.
- Present completed solutions to clients, explaining technical decisions, benefits of said solution, and recommendations for further improvements.
- Mentor junior team members in best practices for machine learning development, Azure AI services, and Azure Kubernetes Service (AKS).
1 Year:
- Lead the development of reusable MLOps frameworks and templates to streamline project setup for future AI engineers in the practice.
- Set standards for model optimization, CI/CD, and containerization, influencing best practices and quality benchmarks for the team.
- Serve as the AI technical lead in strategic client engagements, directly contributing to client satisfaction and project success.
- Proactively identify new business opportunities and suggest enhancements to existing client solutions, demonstrating JourneyTeam’s value as a strategic partner in AI.
- Mentor team members on advanced AI and MLOps practices, fostering a culture of continuous learning and excellence.
- Lead internal training sessions or workshops on emerging Azure AI technologies, promoting knowledge-sharing within the practice.
Compensation:
$150,000 - $165,000 annual salary, dependent on experience and demonstrated consulting abilities.
Benefits:
JourneyTEAM offers a wide range of excellent benefits including healthcare and dental options, as well as a 401k with a ~4% employer match with funds that vest immediately. We enjoy flexible time off and our employees average 3.5 to 4 weeks off a year. We also provide a monthly phone stipend of $25 as well as a gym membership monthly reimbursement of up to $200. We enjoy a culture of collaboration and creative responsibility to solve problems with autonomy.
Professional office and remote working environments available. JourneyTEAM is an Equal Opportunity Employer.
Job Tags
Immediate start, Remote job, Flexible hours,