Data & AI Solutions Lead

Infomineo

. Identify opportunities to apply data analytics and AI services across business functions and client engagements .

Posted 9/19/2026full-timeCairo • EgyptSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in delivering data analytics and AI solutions, including LLM-based systems and multi-agent pipelines, while managing client engagements and project delivery. Proficient in DevOps practices, cloud deployment, and technical proposal development, with a strong focus on solution quality and performance optimization.

Highest-signal resume keywords

Data Analytics Solution DeliveryLLM-Based AI Solutions DesignDevOps Practices (CI/CD, Docker)Technical Proposal DevelopmentProject Management in Client-Facing Context

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLMachine LearningData AnalyticsAI Solution DeliveryMLOpsLLMOpsMulti-Agent PipelinesRAG SystemsCloud Environment Configuration

Soft Skills

Excellent Communication SkillsMentoring and CoachingStakeholder EngagementTeam CollaborationProblem-Solving

Tools & Technologies

LangGraphLangChainGCPAWSAzure

Certifications & Qualifications

Relevant Cloud CertificationsData CertificationsAI Certifications

Industry Keywords

Client EngagementRFP ResponsesAI Governance FrameworksResponsible AI PracticesData Privacy and Security

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

Proven track record in data analytics, data science, or AI solution delivery, with experience owning delivery end-to-end and guiding the work of others typically built over 6 or more years, though readiness is assessed on demonstrated capability rather than years alone
Demonstrated experience delivering technical solutions in a client-facing or stakeholder-facing context, with exposure to a range of technical solution types rather than a single repeated use case
Solid working knowledge of DevOps practices (CI/CD, Docker, cloud environment configuration, monitoring), with the ability to own deployment end-to-end alongside the team
Proven ability to develop and present solution proposals that translate a business need into a defined technical approach, scope, and value case
Hands-on experience designing and delivering LLM-based and agentic AI solutions in production, including multi-agent pipelines, RAG, and tool use
Experience using orchestration frameworks such as LangGraph, LangChain, or equivalent
Strong working knowledge of machine learning
Experience defining evaluation methods for LLM and agent outputs and using them to drive improvement
Ability to reason about and optimize the cost, latency, and reliability of AI systems
Hands-on technical proficiency in Python and SQL
Familiarity with deployment and MLOps/LLMOps practices on at least one major cloud platform: GCP, AWS, or Azure
Solid project management capability managing scope, priorities, resources, and timelines across concurrent initiatives, including estimating effort in man-days
Experience managing or mentoring technical team members
Excellent communication skills in English
Professional proficiency in French is strongly preferred
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field
Experience in a consulting, professional services, or client-delivery environment, including contributing to RFP responses and commercial proposals
Experience building or scaling a data/AI function or Center of Excellence from an early stage
Experience with clients, AI governance frameworks, or responsible AI practices
Relevant cloud, data, or AI certifications are preferred
Working proficiency in Arabic is preferred

Benefits

Comp & perks

A competitive compensation and benefits package
A dynamic and supportive work environment that values leadership, innovation, and your contributions
Continuous learning and professional development opportunities to propel your career forward in data and AI