Data Scientist – Applied AI & Agent Systems Specialist

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.

Key Responsibilities
• 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.
Governance Responsibilities
• 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.
Compliance Responsibilities
• 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.
Data Accountability
• 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.
Systems Accountability
• 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.

Skills:-

Bachelor’s degree in Business Administration, Operations Management, Public Policy, International Development, or a related field.

Strong proficiency in Python (production-level coding skills).

Mnium 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)