Deployment StrategistLocation: Sydney, Australia

Employment: Full-time

Most enterprises are not struggling with AI because the models do not work. They are struggling to identify where AI will create material value, redesign the work around it and bring their people, technology and governance with them. monō closes that gap. We combine an enterprise AI orchestration platform with small, senior pods of engineers and operators who embed inside our clients’ businesses.

We build on client infrastructure, work with the systems they already run and prove value through working capability.

We are looking for a Deployment Strategist to own the transformation from an ambiguous ambition to measurable value, sustained adoption and evidence-led expansion.

The roleAs a Deployment Strategist at monō, you will work directly with client executives, operators, risk leaders and technical teams to determine where AI can materially change how the business performs and then remain accountable for making that change real.

You will build the executive and frontline coalition, shape the business case, direct delivery alongside a Forward Deployed Engineer (FDE), establish how value will be measured and use the evidence to decide whether to scale, pivot or stop.

You will stay close to the workflow and the production reality, working from boardroom priorities through to frontline behaviour. You will be technically substantive enough to challenge assumptions about data, architecture, model behaviour, evaluation, security and controls without pretending to be the engineer responsible for the build.

On any given engagement, the highest-leverage action may be reframing the client’s objective, observing a broken workflow, resolving a conflict between executives, challenging an unsupported value claim, narrowing scope with the FDE, redesigning the operating model or recommending that monō does not expand until the evidence is stronger.

You will have autonomy and accountability for the business outcome.

What you will ownUnderstand the business and find the value

- Learn how the client creates value across revenue, cost, capacity, capital, risk and customer experience.
- Translate a broad executive ambition into a clear transformation thesis tied to business priorities.
- Establish baselines, value mechanisms, accountable owners and evidence requirements before making an investment claim.
- Distinguish capacity released from cash saved, revenue created, losses avoided and risk reduced.
- Build value cases that are transparent about assumptions, attribution, cost, uncertainty and trade-offs and credible under CFO scrutiny.

- Shape a technically credible deployment

- Work as a close pair with an FDE from discovery through production evidence and adoption.
- Connect the intended business outcome to the target workflow, source data, architecture, model behaviour, integrations and human-control model.
- Ask the questions that expose feasibility, security, data-quality, evaluation, latency, cost and operational constraints early.
- Distinguish where deterministic software, AI models and human judgement should each sit.
- Define the acceptance evidence, release boundaries, fallback paths and prohibited actions with the FDE and client owners.
- Know when to challenge,



when to defer to deeper engineering expertise and when uncertainty makes a commitment unsafe.

Turn strategy into an executable outcome
- Convert the transformation thesis into a focused sequence of decisions, owners, dependencies, milestones and gates.
- Secure the access, client capacity and executive commitments needed to move quickly.
- Keep strategy tied to working evidence rather than allowing activity or presentation volume to substitute for progress.
- Adapt scope, sequence or operating model as technical, organisational or commercial facts change.
- Protect trust and the outcome when dependencies fail, sponsors change or early evidence contradicts the plan.

Grow through proven value
- Establish what evidence would justify scaling, extending, pivoting or stopping a deployment.
- Identify the next value pocket jointly with the client, grounded in what the first deployment has proved.
- Partner with GTM on the buyer map, commercial path and account plan while owning the value narrative.
- Expand only when the value, delivery capacity and client commitment support it.
- Say no to work that is infeasible, uneconomic or likely to weaken long-term trust—even when revenue is available.

What you bringWe care more about demonstrated capability than a particular title, degree or employer. You should be able to show that you have:
- Owned a material transformation end to end. You have taken work from an ambiguous mandate through discovery, stakeholder alignment, delivery, adoption and measurable outcome—not only strategy, pre-sales or programme coordination.
- Strong business and economic judgement. You can understand an unfamiliar business model, identify the real constraint and build a defensible value thesis with clear baselines, causal logic and assumptions.
- Deep workflow-discovery skills. You can learn from frontline work, find exceptions and incentives that are invisible in a process map and choose a focused first wedge.
- Technical, data and applied-AI fluency. You can reason credibly about enterprise systems, APIs, data lineage, identity, model limits, retrieval, agents, evaluation, latency, cost, security, auditability and human control. You do not bluff, oversimplify or treat AI as a generic answer.
- Executive influence without formal authority. You can build coalitions across competing interests, improve senior decisions, handle conflict and bad news, and maintain trust under pressure.
- Delivery judgement. You can translate strategy into decisions, owners, sequencing and gates; identify the critical dependency; and adapt when the facts change.
- Operating-model and adoption experience. You understand that roles, incentives, decision rights, controls and capability must change for technology to create sustained value.
- Commercial ownership. You can turn verified outcomes into a credible expansion path, work effectively with GTM and recognise when not to sell.
- High agency and integrity.



You seek evidence, make difficult choices, communicate uncertainty clearly and remain accountable when the plan or value case fails.
- Accountable use of AI tools. You use AI to improve speed and quality while remaining able to explain, verify and revise every material output.

The strongest evidence is a transformation you personally helped move from an unclear problem to an adopted operating change—including the economics, the technical realities, the stakeholders you influenced, what failed and how the next phase became—or did not become—commercially real. Helpful, but not required
- Experience leading AI, data, digital or operating-model transformation in an enterprise environment.
- Experience in financial services, healthcare, government or another regulated or security-sensitive sector.
- Experience in strategy and operations consulting with direct accountability through implementation and value realisation.
- Enterprise product, operations, business-unit or transformation leadership experience.
- Experience in deployment strategy, solutions, customer transformation or enterprise technology where you stayed accountable after the sale.
- Experience as a technical founder, general manager or operator who has sold and delivered complex change.
- Practical experience creating value-measurement models, adoption instrumentation or executive governance.
- Enough hands-on technical experience to inspect data, prototype an idea or interrogate a system design. Coding can be useful, but it is not the primary accountability of this role.

No single background is preferred. We are building a team with different strengths, but every Deployment Strategist must meet a high bar for business judgement, technical credibility, executive leadership and value-led commercial ownership. This role is not
- a strategy role that ends with a deck, roadmap or hand-off;
- a pre-sales role measured primarily by closing the initial opportunity;
- a programme-management role focused on cadence and activity without owning the transformation thesis;
- an account-management role that depends on others to supply the business or technical substance;
- a domain-advisory role that cannot challenge data, architecture, AI behaviour or production constraints; or
- a Forward Deployed Engineer role where you personally own the code and technical implementation.

The Deployment Strategist and FDE work as a pair. You do not hand a finished strategy to engineering, and the FDE does not inherit all stakeholder, value and expansion ownership. You remain accountable from discovery through value proof, adoption and expansion; the FDE remains accountable for the technical path to a secure, adopted production capability. You will partner closely with GTM, but GTM owns the commercial process, contract and forecast. You own the transformation thesis, value narrative, client coalition and evidence-led path to expansion.

Location and travelThis role is based in Sydney. Regular in-person work at monō’s Martin Place office and client sites is an inherent part of forward deployment, and client-site travel may be required. We will discuss the expected cadence and any reasonable workplace adjustments early in the process.

This is not a remote-only role.

📌 Deployment Strategist (Sydney)
🏢 monō ai
📍 Sydney