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✨ About This Role: Design, build, and deploy AI-powered agents and automation systems that enhance the operational intelligence, decision-making, and workflow efficiency. Act as the primary Applied AI Engineer within the Smart Systems & Operational Enablement department, translating business challenges into production-ready AI and agentic solutions. Develop software-driven AI capabilities that integrate securely and reliably into enterprise systems.
Job Responsibility:
Design, build, and deploy AI-powered agents and automation systems that enhance the operational intelligence, decision-making, and workflow efficiency
Act as the primary Applied AI Engineer within the Smart Systems & Operational Enablement department, translating business challenges into production-ready AI and agentic solutions
Develop software-driven AI capabilities that integrate securely and reliably into enterprise systems
Design and build AI agents using LLM APIs (e.g., Azure OpenAI, OpenAI or equivalent)
Develop multi-step orchestration workflows integrating AI models with internal systems and APIs
Implement agent memory systems (vector databases, embeddings, contextual retrieval)
Build and maintain AI-enabled automation using tools such as Python frameworks, n8n, or equivalent orchestration platforms
Develop evaluation frameworks to measure agent performance, accuracy, reliability, and drift
Deploy AI solutions in production environments following enterprise architecture standards
Collaborate with Systems Integration to embed agents within CRM/ERP and operational workflows
Continuously improve AI workflows based on feedback and monitoring insights
Ensure all AI systems follow established AI governance and risk frameworks
Maintain documentation of AI architectures, workflows, and dependencies
Support AI lifecycle management including versioning, logging, and traceability
Collaborate with AI Systems & Governance Specialist to ensure compliance with responsible AI standards
Ensure AI solutions comply with data protection regulations and internal governance policies
Implement safeguards for handling sensitive data within AI workflows
Support auditability by maintaining transparent documentation and logging of AI decisions
Collaborate with Cybersecurity to ensure secure deployment of AI-enabled systems
Ensure AI agents utilize governed and validated datasets
Monitor data drift and model degradation
Validate data pipelines supporting AI workflows in coordination with Data Engineer
Ensure data usage transparency and traceability
Deploy AI services within approved infrastructure environments
Ensure agent integrations align with enterprise integration architecture
Collaborate on performance optimization and reliability improvements
Support testing and validation before production rollout
Requirements:
Bachelor’s degree in Business Administration, Operations Management, Public Policy, International Development, or a related field
Strong proficiency in Python (production-level coding skills)
Minimum 5 years experience in applied AI, machine learning engineering, or AI-driven software development
Experience working with LLM APIs (OpenAI, Azure OpenAI, or equivalent)
Understanding of agentic architectures (tool use, memory, multi-step orchestration)
Experience with API integration and RESTful services
Familiarity with vector databases and embedding workflows
Knowledge of software version control (Git)
Experience with workflow automation/orchestration tools (n8n, LangChain, or equivalent frameworks)
Understanding of testing, logging, monitoring, and production deployment principles
Working knowledge of cloud environments (Azure preferred)