Senior Consultant- Agentic AI Engineer at Deloitte

Lead discussions with business and functional analysts to understand requirements and assess integration impacts on business architecture. Prepare technical architecture and design, clarify requirements, and resolve ambiguities. Develop solutions in line with established technical designs, integration standards, and quality processes. Create and enforce technical design and development guides, templates, and standards. Facilitate daily scrum meetings, manage deliverables, and prepare weekly status reports for leadership review. Conduct detailed deliverable reviews and provide technical guidance to team members. Collaborate with onsite clients, coordinators, analysts, and cross-functional teams. Design templates or scripts to automate routine development or operational tasks.

Key Responsibilities:

• Design and Development: Architect, build, and optimize agentic AI systems (e.g., autonomous agents, multi-agent frameworks, LLM-powered agents).
• Integrate agentic AI solutions with existing enterprise platforms and workflows.
• Research and Experimentation: Evaluate emerging agentic AI models, frameworks, and toolkits.
• Prototype and benchmark agentic AI solutions for scalability, robustness, and safety.
• Deployment and Monitoring: Deploying agentic AI agents in production environments, ensuring reliability and performance.
• Monitor agent behaviors, diagnose anomalies, and refine agent policies as needed.
• Developed feedback loops for continuous agent improvement.
• Ethics and Governance: Ensure agentic AI solutions comply with ethical standards, regulatory requirements, and organizational policies.
• Communicate complex technical concepts to non-technical audiences.

Qualifications

• A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of Second Class Upper/Upper Credit division.
• Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
• 6 - 10 years of hands-on experience in Artificial Intelligence, Machine Learning, or related field.
• Knowledge of developing Gen AI or AI/ML solutions from use case to production and an understanding of agentic or autonomous systems.
• Strong understanding of Infrastructure and DevOps related to Gen AI Use case deployments including Cloud environments, LLM Hosting, CICD deployments, docker and Kubernetes clusters.
• Proficiency in Python development and FastAPI/Flask framework along with SQL
• Familiarity with agentic AI frameworks and concepts - LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), LLMs, Chain of Thought prompting, knowledge store, embeddings.
• Autonomous agent development using cloud-based AI services.
• Prompt engineering techniques and fine-tuning.
• Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
• Experience with cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.