Infomineo

Artificial Intelligence

• Identify opportunities to apply data analytics and AI services across business functions and client engagements
• Evaluate business value, feasibility, and priority of opportunities and translate ambiguous needs into problem statements
• Develop proposals and RFP/RFI responses covering scope, approach, architecture, staffing, estimates, timelines, and expected impact
• Build investment business cases, including trade-offs and risks
• Lead client scoping and discovery workshops and manage scope changes and contract amendments
• Design custom data and AI solutions, including multi-agent pipelines, RAG systems, and LLM-powered workflows
• Own deployment into client and cloud environments, including CI/CD pipelines, containerization, environment setup, and post-deployment monitoring
• Define solution quality measures and build evaluation and validation loops for LLM and agent outputs
• Monitor production performance and drive continuous improvement based on results and user feedback
• Ensure solutions are maintainable, scalable, and reliable
• Manage AI workload cost and performance, including token and compute consumption, cloud spend, and latency
• Build solutions that respect data privacy, security, and responsible AI requirements
• Evaluate emerging data analytics, LLM, agentic framework, MLOps, and LLMOps technologies
• Define and champion technical standards and best practices with department and Tech/R&D leadership
• Lead projects end-to-end, coordinating priorities and allocating resources across concurrent initiatives
• Communicate progress, risks, dependencies, and trade-off decisions to leadership, clients, and stakeholders
• Plan team capacity and staffing and maintain delivery rituals, estimation practices, quality routines, and escalation paths
• Mentor and coach team members through training and career development
• Manage performance and development through 1:1s, feedback, performance conversations, objective setting, and career planning
• Contribute to hiring, onboarding, and retention
• Build a culture of technical rigour, intellectual curiosity, and shared ownership
• Uphold client confidentiality, data protection, information security, company policies, and responsible AI practices

Data & AI Solutions Lead