Job Description
Role Description
An AI Practice Architect is a senior-level solution architect with at least 10 years of
experience in software engineering, including 4 years in AI and Data Science. Their
primary responsibility is to lead, design, and implement comprehensive AI solutions
using Cloud-based AI services, ensuring these solutions align with business objectives
and adhere to technology best practices.
Key Missions
• Align Technology with Business Objectives: Ensure that technical solutions
meet both company and customer business goals.
• Promote Best Practices: Reduce technical debt by advocating for best practices
from design through delivery.
• Foster Innovation: Introduce and integrate cutting-edge technologies to drive
innovation.
• Lead by Example: Actively participate in projects, demonstrating leadership
through hands-on involvement.
Key Responsibilities
• Project Delivery: Play key roles in projects, supporting the project team to
ensure alignment with technology best practices.
• Practice Development: Design and implement end-to-end AI practices,
including technology best practices, solutions, tools, and processes.
• Pre-sales Support: Lead solution development, create work breakdown
structures, and provide estimations during the bidding phase. Promote AI
practices to both internal and external customers.
Success Profiles
Knowledge
• Software Engineering: Expertise in building scalable and robust software
applications. Skilled in designing, implementing, and optimizing systems to
handle high traffic and large data volumes efficiently.
• AI/ML: Understand large language models (LLMs) like Llama, Mistral and AI/ML
frameworks such as TensorFlow, PyTorch, and Scikit-learn. Proficiency in the
full AI/ML lifecycle, including data preparation, model training, deployment,
and monitoring (e.g., MLOps pipelines). Understand AI-driven automation,
including intelligent process automation, predictive analytics, and autonomous
systems.
• Data Engineering: Expertise in building scalable data pipelines and real-time
streaming using tools like Apache Kafka, Flink, and Spark. Strong knowledge of
data orchestration tools (e.g., Apache Airflow, Prefect) and database
optimization (SQL and NoSQL).
• Architecture and Design Patterns: Experience with microservices, event-driven
systems, and serverless architecture. Deep understanding of automationfriendly architecture frameworks and patterns, such as Infrastructure as Code
and self-healing systems.
• Security and Compliance: Knowledge of secure AI, automation, and data
systems, including data governance, GDPR, and SOC 2. Familiarity with
automation for compliance monitoring and reporting.
• Emerging Technologies: Awareness of cutting-edge trends in automation, such
as hyper-automation and low-code/no-code platforms, and their integration
with AI systems.
Experience
• Technical Leadership: Over 10 years in software engineering or technology
roles, with at least 4 yearsin leadership positions related to AI and Data Science.
• AI/ML and Data Systems: Proven track records of delivering AI/ML-powered
solutions, such as intelligent chatbots, fraud detection systems, or workflow
optimization. Hands-on experience in building and managing scalable data
platforms and predictive analytics pipelines.
• Cross-Functional Collaboration: Experience working closely with stakeholders
across engineering, data science, operations, and business functions to deliver
AI and automation solutions.
• Mentorship: Experience guiding engineering teams to adopt best practices in
AI-related areas.
Competency
• Strategic Thinking: Ability to align AI solutions with organizational goals and
long-term strategies.
• Systems Thinking: Expertise in designing solutions that seamlessly integrate AI
services into ecosystems.
• Analytical Skills: Strong ability to solve complex automation and data
challenges while ensuring efficiency and scalability.
• Leadership and Influence: Proven track record of leading multi-disciplinary
teams and influencing stakeholders to adopt AI and automation initiatives.
• Agility and Adaptability: Comfortable navigating dynamic technological
environments and adapting to emerging trends in Cloud, Automation, AI, and
Data.
• Execution Excellence: Demonstrated ability to deliver reliable, scalable AI
solutions on time and within budget.
Personal Attributes
• Visionary: Forward-thinking and able to envision how AI can transform
business processes and drive innovation.
• Collaborative: Skilled at building relationships across teams to deliver
integrated and impactful AI solutions.
• Detail-Oriented: Focused on ensuring the quality, reliability, and security of AI
and data systems.
• Ethical: Committed to the responsible use of AI and automation, ensuring
compliance with ethical and regulatory standards.
• Continuous Learner: Enthusiastic about exploring advancements in AI, data,
and automation technologies and applying them to real-world problems.
• Resilient: Able to handle challenges with persistence and adaptability, driving
successful outcomes in high-pressure environments.
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Offered Salary Negotiable
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Career Level Senior
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Experience 7 Years
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+84 (24) 7307 9999