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Infomineo

AI-powered business research and insights

Data & AI Solutions Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeCairo, Cairo Governorate, EgyptNo salary listed

About the Job

Requirements

  • Proven track record in data analytics, data science, or AI solution delivery, including end-to-end delivery ownership and guiding others, typically developed over six or more years; readiness is assessed on demonstrated capability rather than years alone.
  • Experience delivering technical solutions in client-facing or stakeholder-facing contexts, with exposure to a range of technical solution types.
  • Working knowledge of DevOps practices, including continuous integration and continuous delivery, Docker, cloud environment configuration, and monitoring, with the ability to own deployment end-to-end alongside the team.
  • Ability to develop and present solution proposals translating business needs into a defined technical approach, scope, and value case.
  • Hands-on experience designing and delivering production LLM-based and agentic AI solutions, such as multi-agent pipelines, retrieval-augmented generation, and tool use, using orchestration frameworks such as LangGraph, LangChain, or equivalent, alongside strong working knowledge of machine learning.
  • Experience defining evaluation methods for LLM and agent outputs, such as test sets, quality metrics, and human or model-based review, and using them to drive improvement.
  • Ability to reason about and optimize AI systems' cost, latency, and reliability.
  • Hands-on technical proficiency in Python and SQL, with the depth to design solutions, review team work, and make credible architectural decisions.
  • Familiarity with deployment and MLOps/LLMOps practices, including deployment, monitoring, versioning, and lifecycle management, on at least one major cloud platform: Google Cloud Platform, Amazon Web Services, or Microsoft Azure.
  • Project management capability across concurrent initiatives, managing scope, priorities, resources, and timelines, including effort estimation in man-days.
  • Experience managing or mentoring technical team members and interest in developing others.
  • Excellent English communication skills and the ability to move fluently between business and technical conversations.
  • A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field.

Responsibilities

  • Identify opportunities to apply data analytics and AI services across business functions and client engagements, and proactively surface them to leadership.
  • Collaborate with stakeholders to evaluate each opportunity's business value, feasibility, and priority, translating ambiguous needs into clearly defined problem statements.
  • Develop proposals and RFP/RFI responses covering scope, approach, architecture, staffing, man-day estimates, timelines, and expected impact, and present them to technical and non-technical audiences.
  • Build investment business cases, including the trade-offs and risks of proposed approaches.
  • Lead client scoping and discovery workshops, and manage scope changes and contract amendments when requirements evolve beyond the agreed perimeter.
  • Design custom data and AI solutions for defined business needs, including multi-agent pipelines, retrieval-augmented generation systems, and LLM-powered workflows, selecting appropriate tools, frameworks, architectures, and models.
  • Own deployment of solutions into client and cloud environments, working with the team on CI/CD pipelines, containerization, environment setup, and post-deployment monitoring to ensure production reliability.
  • Define solution-quality measures, build evaluation and validation loops for LLM and agent outputs, monitor production performance, and drive continuous enhancement based on results and user feedback.
  • Ensure solutions are maintainable, scalable, and reliable rather than optimized for a single successful demonstration.
  • Manage AI workload costs and performance, including token and compute consumption, cloud spend, and latency, and make economically sustainable architecture trade-offs.
  • Build solutions that respect data privacy, security, and responsible AI requirements, particularly for public-sector and regulated clients.
  • Stay informed about business applications, tools, and methods in data analytics and AI, including LLMs, agentic frameworks, deployment, MLOps, and LLMOps platforms.
  • Evaluate emerging technologies against organizational needs and introduce those offering genuine advantages, with a clear rationale for adoption.
  • Define and champion technical standards and best practices for building, evaluating, and deploying data and AI solutions, in collaboration with department and Tech/R&D leadership.
  • Lead projects end-to-end, coordinate priorities across concurrent initiatives, and allocate resources according to business impact.
  • Communicate progress, risks, dependencies, and trade-off decisions to the Head of AI & Analytics Services, clients, and other stakeholders.
  • Anticipate delivery risks and drive their resolution.
  • Plan team capacity and staffing across concurrent engagements, match people to projects based on skills, workload, and business impact, and flag resourcing gaps early.
  • Define and maintain team delivery rituals, estimation practices, quality and review routines, and escalation paths, and improve them as the team grows.
  • Mentor and coach the team, providing guidance, training, and career development opportunities.
  • Manage team members' performance and development through regular one-to-ones, feedback, performance conversations, objective setting, and career growth planning.
  • Contribute to team hiring, onboarding, and retention by defining profiles, interviewing candidates, and integrating new joiners.
  • Recognize strong performance and address underperformance constructively and early.
  • Teach team members how to frame problems, choose approaches, and validate results, and empower them to apply these strategies independently.
  • Build a culture of technical rigour, intellectual curiosity, and shared ownership of outcomes.
  • Uphold client confidentiality, data protection, information security, and company policies across engagements, and ensure the team does the same.
  • Apply responsible AI practices, including transparency about model limitations, human oversight, and appropriate use of client data, and raise concerns early when a use case warrants it.

Desired Qualifications

  • Experience in consulting, professional services, or client delivery, 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, such as Google Cloud Professional Machine Learning Engineer or equivalent.
  • Working proficiency in Arabic.
  • Professional proficiency in French.

About the Company

Infomineo

AI-powered business research and insights

Infomineo delivers business insights by combining human expertise with proprietary AI to help clients gain competitive advantage. It blends industry specialists (350+ researchers across 25 nationalities) with its proprietary B.R.A.I.N.™ AI platform (50+ specialized agents and 1,000+ tested prompts) and a large library of knowledge assets (500,000+ case studies and premium subscriptions). Its services span AI-powered business research, data analytics from collection to predictive modeling, and strategic business communication including multi-language translation. The company offers engagement models such as projects, Brainshoring™, and AI advisory, and positions itself as the inventor of Brainshoring™ — a balanced approach that integrates human depth with artificial intelligence to solve problems and create value. With 5 global offices and ISO 27001 certification, Infomineo aims to deliver lasting competitive advantage for clients like EY, PwC, L’Oréal, and The Guardian.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Casablanca, Morocco
Founded
2011

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