What are the responsibilities and job description for the AI Architect position at Tekgence Inc?
Role: AI Solution Architect
Location: Durham, North Carolina, - Onsite if possible, else Remote
Skills: Digital : Amazon Web Service(AWS) Cloud Computing~Digital : Google Cloud~Digital : Azure Machine Learning (ML)
Experience Required: 10 & Above
Role Descriptions:
Must Have Technical/Functional Skills
• Strong expertise in AI/ML concepts including supervised, unsupervised, deep learning, NLP, and generative AI.
• Hands-on experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn.
• Proficiency in programming languages like Python, R, or Java.
• Experience in designing end-to-end AI solutions including model development, validation, deployment, and monitoring.
• Knowledge of cloud platforms (Azure, AWS, GCP) with AI/ML services (e.g., Azure AI, SageMaker, Vertex AI).
• Experience with MLOps practices, CI/CD pipelines, model versioning, and lifecycle management.
• Strong understanding of data engineering concepts (ETL pipelines, big data technologies like Spark, Hadoop).
• Familiarity with APIs, microservices architecture, and integration of AI models into enterprise systems.
• Knowledge of data governance, security, and compliance in AI solutions.
• Experience with BI and visualization tools (Power BI, Tableau) for AI insights.
• Exposure to domain-specific AI applications (publishing, retail, finance, etc.) is a plus.
• Experience in agentic development design and platform knowledge
Roles & Responsibilities
• Define and design AI-driven solution architectures aligned with business objectives.
• Collaborate with stakeholders to translate business requirements into AI use cases and technical solutions.
• Lead end-to-end AI solution development, from data ingestion to model deployment.
• Design scalable and robust AI/ML pipelines and architectures.
• Provide technical leadership and guidance to data scientists, engineers, and developers.
• Evaluate and recommend appropriate tools, platforms, and frameworks for AI implementation.
• Ensure best practices in MLOps, including model monitoring, retraining, and performance optimization.
• Identify and mitigate risks associated with AI models, including bias, drift, and scalability issues.
• Work closely with cross-functional teams to ensure seamless integration with enterprise applications.
• Drive innovation and continuous improvement by staying updated with latest AI trends and technologies.
• Support pre-sales, solutioning, and proposal development where required.
• Generic Managerial Skills, If any
• Strong stakeholder management and communication skills.
• Ability to lead cross-functional teams and drive collaboration.
• Excellent problem-solving and decision-making abilities.
• Experience in project planning, estimation, and delivery management.
• Strong analytical thinking and strategic mindset.
• Ability to mentor and coach team members.
• Effective risk management and escalation handling