New opportunity

Principal Solution Advisor - AI and Agentic

Cevo · Sydney, Australia

About this role

Cevo seeks a Principal Solution Advisor to shape and lead high-value AI and agentic systems opportunities for enterprise and government clients. The Sydney-based role is hybrid and full-time, connecting cloud, data, modernisation and intelligent automation capabilities to practical business outcomes.

Responsibilities

  • Originate and shape AI-led opportunities; lead assessments, discovery workshops, architecture reviews and executive discussions to define transformation roadmaps, target-state architectures and adoption pathways.
  • Partner with Growth, Presales and Practice leaders on solution strategy, estimates, proposals, statements of work and presales materials. Own outcomes for strategic engagements and provide architecture guidance and hands-on technical direction for AI-assisted engineering.
  • Advise technical and executive stakeholders, develop AI and agentic adoption strategies, and identify adjacent opportunities in platform engineering, cloud evolution, data intelligence and intelligent modernisation.
  • Lead the practitioner community and develop reusable intellectual property, accelerators, reference architectures, delivery frameworks and scalable service offerings. Coach and mentor consulting teams.

Required capabilities:

  • Deep expertise across AI, agentic solutions, cloud, modernisation and data; strategic advisory and commercial skills spanning opportunity origination, scoping, risk management and delivery governance.
  • Ability to coordinate multiple practices, lead workshops and roadmap discussions, produce C-level reports and presentations, and build trusted relationships with stakeholders from engineers to executives.
  • Working knowledge of AI-assisted engineering and agentic tooling; exposure to AWS AI/ML services, including SageMaker and Bedrock, and emerging agentic frameworks. Experience developing business cases and assessing ROI and decision metrics for AI-led transformation is sought.

Preferred

AWS certifications in AI/ML or Solutions Architecture, such as AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect – Professional.

Cevo offers a $2,500 annual technology allowance, $2,000 annually for professional courses and two paid days for courses and exams. Candidates must have unrestricted local working rights.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Agentic AIAI-assisted engineeringAWS SageMakerAmazon BedrockAWS AI/ML servicesCloud architectureSolution architectureStrategic advisoryPresalesSolution shapingDiscovery workshopsArchitecture reviewsTechnical roadmappingExecutive stakeholder engagementBusiness case developmentROI analysisRisk managementDelivery governanceCoachingMentoring

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A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Shape high-value AI opportunities

    The role identifies and leads AI and agentic opportunities, connecting cloud, data, modernisation and automation to customer problems. Prepare to explain how you would distinguish a valuable use case from a technology-led pitch.

  • Turn discovery into an adoption plan

    Cevo calls for assessments, workshops, architecture reviews and executive discussions that produce target-state architectures, roadmaps and practical adoption pathways. Prepare a clear approach for moving from an uncertain starting point to phased decisions.

  • Make pursuits commercially deliverable

    The advisor works with Growth, Presales and Practice leaders on strategy, estimates, proposals and statements of work, then owns strategic engagement outcomes. Prepare to connect scope, business-case metrics, risks and delivery governance.

  • Build capability beyond individual engagements

    The role leads the practitioner community and develops reusable IP, accelerators, reference architectures and scalable service offerings, while coaching teams. Prepare to describe how lessons from delivery could become useful, repeatable assets.

Likely challenges to think through

  • Balance agentic ambition with practical adoption

    A likely challenge is deciding when an agentic approach adds enough value to justify its complexity versus a simpler AI or automation approach. Prepare decision criteria covering the business outcome, architecture, risks and measurable ROI; this is a preparation hypothesis, not a reported Cevo problem.

  • Align multiple practices without blurring accountability

    Integrated propositions may require Growth, Presales, Practice Leads and Delivery to agree on scope and estimates while preserving clear ownership of engagement outcomes. Prepare an example approach for surfacing dependencies, resolving trade-offs and defining decision points.

  • Balance bespoke advice with repeatable offerings

    Enterprise and government clients may have different needs, while the role also calls for scalable services and reusable IP. Prepare to explain which architecture or delivery patterns could be standardised and where discovery should drive client-specific choices.

03

Practice your answers

Technical practice

Suggested practice question: How would you assess whether an enterprise problem is a good fit for an AI or agentic solution?

What to coverThe role leads AI and agentic assessments and discovery workshops. Suggested answer focus: establish the business problem, available data, existing workflows, success measures and risks before recommending an approach.

Suggested practice question: How would you design a target-state architecture connecting agentic AI with cloud, data and modernisation work?

What to coverThe posting calls for integrated customer propositions and target-state architectures. Suggested answer focus: explain the major components, their dependencies and the trade-offs between a focused initial solution and a broader transformation.

Suggested practice question: When would you recommend an agentic approach rather than a simpler AI-assisted workflow?

What to coverCevo seeks advice on both agentic systems and AI-assisted engineering. Suggested answer focus: compare the value of autonomous steps against added complexity, oversight needs and the ability to evaluate outcomes.

Suggested practice question: How would you evaluate where SageMaker, Bedrock or an emerging agentic framework fits in a proposed solution?

What to coverThe posting names exposure to these AWS services and agentic frameworks. Suggested answer focus: start with the workload and integration needs, then explain how you would validate service fit, limitations and delivery risk rather than assume one tool is always appropriate.

Suggested practice question: What technical direction would you give a team introducing AI-assisted engineering into a modernisation engagement?

What to coverThe role provides hands-on technical direction for AI-assisted engineering. Suggested answer focus: describe suitable engineering tasks, review practices and ways to check whether the work improves delivery outcomes.

Suggested practice question: How would you turn discovery findings into a phased AI adoption roadmap?

What to coverThe role defines transformation roadmaps and practical adoption pathways. Suggested answer focus: sequence prerequisites, initial use cases and later capabilities, making dependencies and decision points clear to technical and executive audiences.

Suggested practice question: How would you build a business case and assess ROI for an AI-led transformation?

What to coverThe posting explicitly seeks business-case experience and an understanding of ROI and decision metrics. Suggested answer focus: identify a baseline, expected benefits, delivery and operating costs, uncertainty and measures that could support a continue-or-change decision.

Suggested practice question: How would you scope and estimate a multi-practice AI engagement for a proposal or statement of work?

What to coverThe role contributes to estimates, proposals and statements of work alongside Growth, Presales and Practice leaders. Suggested answer focus: make assumptions, deliverables, responsibilities, dependencies and risks visible, including where discovery must precede a firm estimate.

Suggested practice question: What would you examine in an architecture review of a strategic agentic engagement?

What to coverThe role leads architecture reviews, owns strategic engagement outcomes and brings risk management and delivery governance experience. Suggested answer focus: test alignment with the business objective, integration and data dependencies, operational risks and evidence needed before proceeding.

Suggested practice question: How would you turn lessons from one AI engagement into a reusable service offering?

What to coverCevo calls for accelerators, reference architectures, delivery frameworks and repeatable IP. Suggested answer focus: distinguish reusable patterns from client-specific work, and explain how you would validate practical value before scaling an offering.

Behavioural practice

Suggested practice question: Tell me about a time you shaped an ambiguous customer opportunity into a clear proposal.

What to coverOpportunity origination and solution shaping are central to this role. Use a real example covering the situation, your discovery and scoping actions, and the resulting decision or outcome.

Suggested practice question: Tell me about a time you aligned multiple specialist teams around one customer solution.

What to coverThe posting calls for coordinating Growth, Presales, Practice Leads and Delivery across technology domains. Describe the situation, how you resolved differing priorities or assumptions, and what resulted.

Suggested practice question: Tell me about a time you explained a complex technical trade-off to an executive audience.

What to coverThe role includes executive advisory and C-level reports and presentations. Give the situation, how you adapted your explanation and recommendation, and the decision or feedback that followed.

Suggested practice question: Tell me about a time you helped a practitioner community or consulting team build a new capability.

What to coverCevo calls for mentoring, knowledge sharing and capability growth across practices. Explain the need, your specific coaching or reusable-material contribution, and the observable result.

Suggested practice question: Tell me about a time you took ownership when a strategic engagement faced a significant delivery risk.

What to coverThe role owns engagement outcomes and calls for risk management and delivery governance. Describe the situation, how you surfaced and addressed the risk with stakeholders, and what happened next.

02

Sharpen your knowledge

Topics to prepare

  • AI and agentic opportunity assessment

    The role leads AI and agentic assessments and shapes high-value opportunities. Revision exercise (suggestion): take a hypothetical enterprise problem and explain when an agentic approach would add value, what evidence an assessment needs, and when a simpler approach would suffice.

  • Integrated cloud, data and modernisation architecture

    Cevo asks for cohesive propositions spanning AI, cloud, data, modernisation and intelligent automation. Revision exercise (suggestion): sketch a target-state architecture for a hypothetical client, identifying dependencies and a practical adoption sequence.

  • Commercial shaping and delivery governance

    The posting calls for presales, scoping, risk management, estimates, statements of work and delivery governance. Revision exercise (suggestion): review a hypothetical pursuit and identify its scope boundaries, estimation assumptions, principal risks and governance decisions.

  • AWS AI/ML and agentic tooling choices

    The posting seeks exposure to SageMaker, Bedrock and emerging agentic frameworks, plus working knowledge of AI-assisted engineering. Revision exercise (suggestion): compare where SageMaker and Bedrock might fit in a proposed solution and explain what would need validation before selecting agentic tooling.

  • Repeatable offerings and practitioner capability

    The role develops scalable service offerings, reusable IP and reference architectures while leading a practitioner community. Revision exercise (suggestion): outline what could be standardised from one hypothetical engagement and what must remain client-specific.

Skills to revise

  • Facilitate a discovery workshop

    The role explicitly leads discovery workshops with technical and executive stakeholders. Practice exercise (suggestion): draft an agenda and questions that uncover the business problem, current architecture, decision-makers, constraints and desired outcomes.

  • Turn an architecture review into a roadmap

    Architecture reviews, target-state architectures and adoption pathways are stated responsibilities. Practice exercise (suggestion): use a hypothetical current state to produce a one-page target state, key gaps and phased roadmap.

  • Shape a presales proposal

    The role contributes to solution strategy, estimates, proposals and statements of work alongside Growth, Presales and Practice leaders. Practice exercise (suggestion): draft a concise engagement scope with deliverables, assumptions, estimate rationale and exclusions.

  • Build an AI transformation business case

    The posting seeks experience with business cases, ROI and decision metrics. Practice exercise (suggestion): calculate a simple illustrative ROI from stated assumptions, then show which uncertain costs or benefits could change the decision.

  • Present an executive recommendation

    The role requires C-level reports and presentations and advice across technical and executive audiences. Practice exercise (suggestion): deliver a brief recommendation covering the business outcome, architecture choice, risks and next decision; then prepare a separate technical explanation.

  • Guide technical work and share reusable lessons

    Cevo expects hands-on technical direction for AI-assisted engineering, mentoring and community knowledge-sharing. Practice exercise (suggestion): review a hypothetical implementation approach, record actionable architecture feedback and turn one lesson into a short practitioner briefing.

04

Your preparation checklist

  • Prepare an AI opportunity walkthrough

    The role involves originating and shaping AI-led engagements. Prepare a walkthrough of a relevant example, if available, covering the customer problem, stakeholders, options considered, your contribution and measurable outcomes; distinguish results from estimates.

  • Rehearse a discovery workshop

    Cevo expects this advisor to lead assessments and workshops. Draft a sample agenda and questions that uncover business value, data and cloud constraints, adoption barriers and decision-makers; finish with a proposed roadmap outline.

  • Sketch a target-state architecture

    The role calls for architecture guidance across AI, agentic systems, cloud, data and modernisation. As a practice exercise, diagram a hypothetical solution and explain where Bedrock, SageMaker or agentic tooling might fit, including trade-offs and technical risks.

  • Build a sample pursuit brief

    The posting names estimates, proposals, statements of work and delivery governance. Prepare a one-page illustrative scope with assumptions, work phases, dependencies, risks and decision points, plus a business-case outline showing how ROI would be assessed.

  • Practice an executive-level presentation

    Cevo asks for C-level reports and presentations. Turn the sample opportunity into a short briefing that links the business problem to options, expected value, risks and an adoption pathway; be ready to explain the technical details separately.

  • Collect leadership and reusable-IP examples

    The role includes mentoring, practitioner-community leadership and scalable offerings. Identify examples you can substantiate of coaching or cross-practice collaboration, and outline how a reusable architecture, accelerator or delivery framework could be applied beyond one engagement.

  • Draft questions for Cevo

    Ask how Growth, Presales, Practice leaders and Delivery collaborate on strategic pursuits, how engagement outcomes are measured, and which AI and agentic adoption challenges clients are bringing to the team. These are questions to ask, not assumptions about Cevo’s processes.

AI-generated from the job information · Prepared Sep 30, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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