AI SENIOR SOLUTIONS ARCHITECT

## AI SENIOR SOLUTIONS ARCHITECTApplylocations: Alpharetta - HQtime type: Full timeposted on: Posted 7 Days Agojob requisition id: R-100526**Job Description:**# Key Responsibilities## AI & Enterprise Application Strategy* Define an AI/ML adoption roadmap across ERP, CRM, HRIS, BI, and custom applications.* Translate strategic objectives into use-case-driven AI initiatives, leveraging GenAI capabilities for tangible business value.* Advise IT leadership on emerging AI trends, frameworks, and platform innovations (e.g., LLM orchestration, multi-modal AI).## Architecture & Integration* Architect end-to-end AI solutions in Microsoft Azure AI, integrating with enterprise systems via REST APIs, GraphQL, and event-driven architectures.* Ensure compatibility with solutions running in AWS SageMaker and hybrid-cloud deployments.* Assist with design data ingestion and preparation pipelines.## CI/CD, MLOps & Team Leadership* Lead a team of engineers and data scientists in delivering complex AI projects (e.g., document intelligence, NLP chatbots, predictive analytics, RPA workflows).* Implement MLOps practices and CI/CD pipelines using GitHub Actions for AI model lifecycle management.* Establish model monitoring, retraining schedules, and drift detection with frameworks like MLflow and Kubeflow.## Project Delivery* Own AI project delivery from PoC to production, ensuring robust governance, risk management, security, and compliance.* Deploy scalable models in Azure AI Studio and productionize via APIs or microservices in Kubernetes/AKS.## Stakeholder & Vendor Engagement* Collaborate with Business Analysts, Product Owners, Developers, and Data Engineers to ensure solutions meet functional and performance requirements.* Partner with external AI vendors, cloud providers, and technology partners to align on deliverables and integrations.## Technical Excellence* Hands-on evaluation and selection of AI/ML frameworks (PyTorch, TensorFlow, scikit-learn) and GenAI orchestration tools (LangChain, Semantic Kernel).* Review and approve solution architecture and code for scalability, efficiency, and security compliance.* Mentor and develop team members through training on AI frameworks, cloud development practices, and architectural patterns.## Governance & Security* Assist with implementation of AI-specific data governance, privacy policies, and responsible AI principles.* Ensure compliance with standards and regulations (GDPR, SOC 2, ISO 27001) and practices such as OAuth2, SAML, RBAC/ABAC, encryption-at-rest/in-transit.## Innovation* Initiate and lead rapid Proofs of Concept (PoCs) and Minimum Viable Products (MVPs) using AI and GenAI for streamlined business processes.* Explore and pilot new AI features in LLMs, vision models, speech-to-text, translation, and personalization engines.# Required Qualifications* Bachelor's or Master's degree in Computer Science, Data Science, AI/ML Engineering, or a related technical field.* 5+ years in enterprise IT/applications management with at least 5+ years in AI/ML solution delivery in production environments.* Proven track record leading cross-functional technical teams on complex AI/ML projects in diverse, matrixed enterprise environments.* Deep experience with enterprise application platforms including CRM (Salesforce), ERP (NetSuite, SAP, Oracle), HRIS (Workday), and PSA/Billing (Certinia).* Demonstrated expertise in GenAI, NLP, RPA, predictive modeling, computer vision, and recommendation systems.* Strong understanding of enterprise integration patterns, event-driven architecture, and data engineering principles.* Experience working in regulated or compliance-sensitive environments (SOC 2, GDPR, ISO 27001).* Ability to balance hands-on technical delivery with strategic planning and executive-level communication.* Strong project ownership and accountability with experience in end-to-end delivery from requirements through post-production support.# Technical Requirements## Languages & Frameworks* Advanced Python proficiency including async patterns, data manipulation (pandas, NumPy), and REST API development (FastAPI, Flask).* Working knowledge of Java, C#, or Go for enterprise integrations and microservices development.* Hands-on experience with AI/ML frameworks: TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers.* GenAI orchestration tools: LangChain, Semantic Kernel, LlamaIndex; experience with prompt engineering and RAG architecture design.## Cloud & Infrastructure* Expertise in cloud-native architecture on Microsoft Azure: Azure AI Studio, Azure Machine Learning, Azure OpenAI Service, Azure Data Factory, Synapse Analytics, AKS, Azure Functions.* Hands-on experience with AWS ML services: SageMaker, Bedrock, Lambda, S3, and hybrid-cloud deployment patterns.* Container orchestration: Kubernetes (AKS/EKS), Docker, Helm charts for ML model deployment.* Infrastructure-as-Code: Terraform, Bicep, or ARM templates for reproducible environment provisioning.## Integration & Data* Integration patterns: REST APIs, gRPC, GraphQL, message queues (Kafka, Azure Service Bus, RabbitMQ), and webhook-based architectures.* Data streaming and batch pipeline design using Azure Data Factory, Databricks, Synapse Analytics, and Spark.* Experience designing vector databases and embedding pipelines for RAG/semantic search (Azure AI Search, Pinecone, Weaviate).* Familiarity with data lakehouse patterns and medallion architecture (Bronze/Silver/Gold).## MLOps & DevSecOps* CI/CD pipeline implementation for AI/ML workloads using Azure DevOps, GitHub Actions, or Jenkins.* MLOps platforms: MLflow, Kubeflow, Azure ML Pipelines including model registry, versioning, and experiment tracking.* Model monitoring, drift detection, and automated retraining pipelines.* Security tooling: IAM/RBAC, OAuth2/SAML implementation, encryption-at-rest and in-transit, vulnerability scanning (Snyk, Dependabot).## Automation & RPA* Experience with process automation platforms: Power Automate, UiPath, Blue Prism including AI-augmented workflow design.* Familiarity with Microsoft Power Platform (Power Apps, Power Automate, Copilot Studio) for low-code AI integration.# Desired Skills* Exceptional communication across technical and executive levels — able to translate complex AI concepts into business value narratives.* Demonstrated track record in change management for enterprise AI adoption, including stakeholder readiness, training, and cultural enablement.* Advanced problem-solving skills, particularly in scaling AI workloads from prototype to production under enterprise constraints.* Ability to architect AI reference patterns, reusable components, and drive enterprise-wide standards adoption.* Experience building and presenting business cases for AI investments, including ROI modeling, TCO analysis, and risk framing.* Familiarity with AI agent frameworks (AutoGen, CrewAI, OpenAI Assistants API) and multi-agent orchestration patterns.* Exposure to AI governance frameworks (NIST AI RMF, EU AI Act, Microsoft Responsible AI Standard) and enterprise AI policy design.* Experience with Salesforce Einstein, Agentforce, or Salesforce AI capabilities a plus given enterprise CRM environment.* Contributions to open-source AI projects, published research, or conference presentations a distinguishing factor.* Relevant certifications: Microsoft Azure AI Engineer (AI-102), AWS Certified ML Specialty, Google Professional ML Engineer, or equivalent.Kaleris is an equal opportunity employer. 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