Ai Solutions Architect

**Key Responsibilities**

**Technology Standards, Research & AI Architecture**
- Continuously research and evaluate emerging AI/ML technologies, frameworks, and best practices to ensure Agile Dream Team remains at the forefront of innovation.
- Test and validate new AI, MLOps, and automation tools before integrating them into company workflows.
- Define and implement AI technology stacks, best practices, and workflows to ensure consistency and efficiency across AI/ML projects.
- Lead AI/ML architecture design for enterprise solutions, ensuring scalability, security, compliance, and cutting-edge advancements.
- Establish company-wide standards for AI model development, deployment, and operationalization to enhance efficiency and reduce technical debt.

**AI & Data Strategy Leadership**
- Collaborate with Dream Labs AI to refine AI strategies, create roadmaps, and explore new AI-driven business models.
- Conduct AI readiness assessments and provide clients with clear implementation roadmaps for AI adoption.
- Define strategies for predictive analytics, generative AI, AI agents, and enterprise AI integration, ensuring solutions align with business needs.
- Lead efforts to transition the company toward AI-driven business models, including value-based billing and AI-powered efficiency improvements.

**Project Estimation, Technical Consulting & Innovation Adoption**
- Work closely with sales and project teams to provide accurate AI project estimations, covering scope, cost, and timeline.
- Develop methodologies for value-driven AI solutions, ensuring alignment between business impact and technical feasibility.
- Test, prototype, and advocate for the adoption of cutting-edge AI technologies, ensuring Agile Dream Team is an industry leader in AI-driven development.
- Support client engagements by defining scalable AI architectures, optimizing cloud-based AI solutions, and integrating AI into enterprise systems.

**Mentorship, Thought Leadership & Research**
- Act as a technical mentor to AI/ML engineers, data scientists, and MLOps practitioners, fostering a culture of continuous learning.
- Lead internal training, research initiatives, and workshops on AI, MLOps, CloudOps, and emerging AI trends.
- Establish a framework for continuous R&D in AI, ensuring the company is always ahead of industry advancements.
- Publish and share insights on AI trends, best practices, and technological breakthroughs, positioning Agile Dream Team as a thought leader in AI innovation.

**Collaboration & Cross-Functional Leadership**
- Work closely with Agile Delivery Teams to ensure AI solutions align with Agile and DevOps methodologies.
- Collaborate with Data & Cloud Engineering teams to integrate AI models into enterprise systems.
- Support the Dream Labs AI mission of fostering AI-driven transformation across industries through research and experimentation.

**Required Qualifications**:

- 7+ years of experience in AI/ML engineering, MLOps, or AI architecture.
- Expertise in AI/ML frameworks (TensorFlow, PyTorch, Hugging Face) and MLOps tools (MLflow, Kubeflow, SageMaker Pipelines).
- Strong experience with cloud AI platforms (AWS, Azure, GCP) and AI model deployment strategies.
- Deep knowledge of data engineering, AI infrastructure, vector databases, and Retrieval-Augmented Generation (RAG).
- Proven ability to design AI architectures that balance performance, scalability, and compliance.
- Experience in AI governance, bias detection, model explainability, and ethical AI practices.
- Hands-on experience with AgentOps, AI agents, and enterprise AI solutions.
- Ability to mentor technical teams, lead research efforts, and drive AI innovation.
- Experience in estimating AI projects and defining technical proposals for clients.
- Strong problem-solving skills and ability to proactively integrate new AI technologies into enterprise workflows.

**Preferred Qualifications**:

- Certification in AI/ML cloud services (AWS Machine Learning Specialty, Azure AI Engineer Associate, Google Cloud AI Engineer).
- Previous experience leading AI innovation labs or research teams.
- Deep understanding of enterprise AI compliance frameworks and best practices.

Work Location: In person