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Salary
≈ $37k – $87k per year (Estimated)
Location
Hybrid (Lisbon, Portugal)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Jun 18, 2026. Efficio Consulting scores C on the Alion truth index.

Overview
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Impact
Profile match
Efficio’s procurement consulting services drive lasting results in a rapidly evolving global market.

We are looking for a Data & AI Consultant to join a fast-growing client-facing technology team. This is not a traditional data engineering role, and it is not a pure consulting role. It sits at the intersection of engineering, AI implementation, technical advisory, and client delivery.

You will work directly with a major global client, helping them understand, design, and implement AI-enabled solutions within their own data and technology environment. Rather than simply building products in isolation, you will guide stakeholders through the journey from problem definition to roadmap creation, MVP development, and scalable implementation.

This role is ideal for someone who enjoys both building and advising: someone who can speak confidently with senior stakeholders, translate business problems into technical roadmaps, and work hands-on with Python, AWS, APIs, databases, CI/CD pipelines, and AI models.

What you'll do:

    As a Data & AI Consultant, you will play a key role in shaping and delivering AI-enabled data solutions for a major client. Your responsibilities will vary depending on the workstream, but will typically include:

    • Working directly with client stakeholders, from senior leaders and board-level audiences to technical teams and day-to-day users, to understand business problems and translate them into practical technical solutions.

    • Supporting the definition of AI and data workstreams, including requirements gathering, technical discovery, roadmap creation, prioritisation, and implementation planning.

    • Designing and developing MVPs that demonstrate how AI, data pipelines, APIs, and cloud infrastructure can be used to solve real client problems.

    • Guiding client and partner engineering teams on how to build, integrate, and scale solutions within their own data pipelines and technology environment.

    • Acting as a bridge between business stakeholders, product teams, external engineering teams, and internal Efficio specialists.

    • Advising on the use of AI models within data engineering processes, including prompting, AI engineering patterns, workflow automation, and integration into production pipelines.

    • Supporting solution design across AWS, Python-based applications, databases, APIs, CI/CD pipelines, and scalable data infrastructure.

    • Bringing a consulting mindset to delivery: structuring ambiguity, communicating clearly, preparing presentations, and helping stakeholders make informed decisions.

    • Contributing to Efficio’s broader technology and IP ecosystem, including selected touchpoints with internal tools and products such as contract review and procurement intelligence capabilities.

What we are looking for:

  • Experience in a technical consulting, data engineering, AI engineering, analytics engineering, backend engineering, or solution engineering role.
    • Strong Python skills and experience building robust, maintainable technical solutions.

    • Experience working with cloud environments, ideally AWS.

    • Practical understanding of data pipelines, databases, APIs, CI/CD practices, and production-quality engineering.

    • Familiarity with AI engineering concepts, such as prompt engineering, LLM integration, RAG patterns, model-enabled workflows, or using AI models within data and analytics processes.

    • The ability to understand complex business problems and translate them into technical roadmaps, implementation plans, and delivery milestones.

    • Confidence communicating with both technical and non-technical stakeholders, including senior client audiences.

    • Experience creating technical documentation, presentations, solution designs, or delivery plans.

    • Comfort working in ambiguity, especially in an early-stage or evolving role where structure is still being defined.

    • A willingness to be hands-on when needed, whether that means building an MVP, reviewing architecture, working with APIs, or supporting implementation decisions.

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