AI Data Architect
Bramcolm, LLC
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Benefits offered by this job
Job summary
Qualifications
- Minimum of 5 years of experience in AI/ML architecture, data engineering, or similar roles.
- Proven expertise with the Azure ecosystem and MLOps tools.
- Strong analytical and problem-solving skills with attention to detail.
Responsibilities
- Architect and integrate AI capabilities into enterprise platforms and analytics dashboards.
- Lead proof-of-concept initiatives for emerging AI technologies.
- Design secure, scalable AI/ML solutions using Azure.
Skills
Education
Tools
Job description
Founded in 2003, Bramcolm, LLC has been at the forefront of IT solutions for two decades, consistently delivering cutting‑edge services tailored to meet the evolving needs of businesses. Based in Indianapolis, IN, our boutique firm has built a reputation for excellence in the IT services and consulting industry.
At Bramcolm, we are committed to leveraging advanced technologies such as AI, machine learning, and cloud computing to deliver efficient, scalable, and user‑friendly solutions. Our collaborative approach involves working closely with clients to understand their unique needs and tailor our services accordingly. We value creativity, agility, and excellence, fostering a culture that encourages continuous learning and growth.
The Bramcolm team is seeking an AI Data Architect who’s excited to shape the future of artificial intelligence. In this role, you’ll put your expertise to work building secure, scalable AI platforms in the Microsoft Azure ecosystem – driving real‑time analytics, predictive insights, optimization, and operations. You’ll collaborate with data scientists, engineers, and business leaders to bring innovative ideas to life while keeping reliability and sustainability at the center.
The right person will blend deep AI/ML and cloud know‑how with an understanding of complex compliance and operational needs. If you’re ready to lead at the crossroads of cutting‑edge technology and critical infrastructure, we’d love to talk.
Given our support for a diverse range of clients, you will have the opportunity to engage in projects across different domains. This means the role may involve participation in entirely unrelated projects, requiring a high degree of flexibility and adaptability. You will need to quickly understand new data sources, business processes, and industry‑specific requirements to deliver effective AI‑driven solutions.
- Architect and integrate AI capabilities into enterprise platforms, management tools, monitoring systems, and analytics dashboards
- Lead proof‑of‑concept initiatives for emerging AI technologies and their application to operations
- Partner with data scientists and engineers to implement ML models with MLOps best practices in Azure
- Design and deploy secure, scalable AI/ML solutions using Azure ML, Azure OpenAI, and Cognitive Services
- Work side by side with Enterprise Architecture to ensure every solution aligns with the company’s long‑term strategy and technology roadmap
- Propose new solutions that can serve multiple teams, while documenting the “why” behind architectural choices so everyone is aligned
- Establish MLOps frameworks using tools like MLflow, Azure DevOps, and CI/CD automation for AI/ML pipelines
- Develop and manage end‑to‑end data pipelines supporting AI/ML workloads—ensuring efficient ingestion, transformation, and model deployment
- Design secure, scalable solutions using data modeling, ETL processes, data warehousing, APIs, and event/stream processing
- Leverage Azure ecosystem tools including Synapse, Data Factory, Data Lake, and Azure Analysis Services
- Implement data quality controls, validation checks, and monitoring mechanisms to maintain accuracy and model performance
- Enforce data security measures, privacy regulations, and industry compliance standards within all AI solutions
- Mentor business teams, partners, and domain experts while setting clear frameworks, guardrails, and accelerators that make delivery smoother and faster
- Communicate across all levels of the organization, lead critical discussions on cost and technology tradeoffs, and champion continuous improvement
- Adapt rapidly to projects spanning various domains, aligning each AI solution with project‑specific business goals
- Continuously learn and adopt new tools, technologies, and methodologies to stay ahead of the curve in AI/ML advancements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
- Minimum of 5 years of experience in AI/ML architecture, data engineering, or similar roles
- Proven expertise with the Azure ecosystem, including Azure ML, Synapse, Data Factory, Data Lake, Azure Cognitive Services, Azure OpenAI, and MLOps tools such as MLflow and Azure DevOps
- Proficiency in programming languages: Python, R, SQL
- Experience with data visualization tools: Power BI, Tableau, or Azure Analysis Services
- Deep understanding of cloud‑native design (IaaS, PaaS, SaaS)
- Hands‑on experience with CI/CD automation for data and AI solutions
- Designing secure, scalable solutions using data modeling and ETL processes, data warehousing architectures, RESTful APIs and microservices, event streaming and real‑time processing
- Understanding of data security, privacy regulations, and compliance standards
- Experience with infrastructure as code (IaC) tools such as Terraform, ARM templates, or similar
- Strong analytical and problem‑solving skills with attention to detail
- Excellent communication and presentation abilities
- Ability to align AI adoption with business goals and mentor cross‑functional teams
- Proven track record of leading technical initiatives and driving innovation
- Demonstrated ability to communicate complex technical concepts to non‑technical stakeholders
- Knowledge of data governance, metadata management, and quality frameworks
- Experience with natural language processing (NLP) and large language models (LLMs)
- Familiarity with computer vision applications and Azure Cognitive Services
- Experience with Kubernetes, Docker, and containerized AI/ML deployments
- Certifications such as:
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure Solutions Architect Expert
- AWS Certified Machine Learning – Specialty
- Google Professional Machine Learning Engineer
- Opportunity to work on cutting‑edge AI/ML projects across diverse industries
- Exposure to emerging technologies and AI innovations
- Continuous learning and professional development opportunities
- Mentorship and leadership development
- Collaborative, agile team culture
- Flexible work arrangements (remote options available)
- Modern technology stack and tools
- Direct impact on client success and innovation
- Competitive salary commensurate with experience
- Conference and training opportunities
- Must be legally authorized to work in the United States
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