Aistra
Website:
aistra.com
Job details:
About the Company
Aistra is an AI transformation and deployment company operating across India, MENA, the UK and Australia. We take clients through all four stages of AI transformation: strategy and roadmap, solution build, production deployment, and operations at scale. Most firms pick one of those and call it a practice. Delivery runs on 80 assets of registered IP, spanning accelerators, toolkits and codified domain playbooks, carried into engagements by embedded pods rather than sold as a slide pack. Aistra Talent builds and calibrates that workforce against defined role archetypes and places them directly into client teams. The Forward Deployed Consultant is the archetype that carries the commercial thread. Everything the pod builds has to survive a conversation this person had first.
About the Role
Most AI business cases fall apart in the same room. Not the workshop where the ideas get generated, the meeting where the CFO asks where the number came from. The benefit is a percentage borrowed from a vendor deck, the baseline was never measured, and nobody can name which line of the P&L moves or in which quarter. The programme gets deferred, or funded at a fraction of the ask, and the technology was never the reason.
That is the problem this role exists to solve. The Forward Deployed Consultant carries the business thread of an engagement end to end. You find where AI moves a real P&L lever, size and defend the case in a form a CFO will accept, write the response that wins the work, specify what gets built, build the prototype that sells it, and stay through delivery until the value shows up in the client's numbers.
This is a forward deployed role, based in India and deployed across India, MENA, the UK and Australia, for people with three to seven years behind them. You work inside the client's environment, alongside their people, onsite or remote as the engagement requires. Expect to rotate across engagements, sectors and geographies.
The role is AI-native in practice, not in description. You build your own demo-grade prototypes rather than briefing someone to build them, and you use AI tooling across research, modelling, drafting and analysis, because the proposal deadline is real and nobody is going to move it for you.
The role is not tiered. There is no version of this job where you run the analysis while a partner owns the client and a delivery lead owns the outcome. You own the diagnosis, the case, the win, the specification, the delivery and the number it lands on.
Responsibilities
- Build the commercial view of the client, from the outside before access or from the inside once embedded, identify where AI moves a real P&L lever, and prioritise the opportunities worth pursuing.
- Size and defend the business case: baseline, value drivers, cost to serve, productivity and headcount effects, payback and sensitivity, in a form a CFO will accept.
- Own RFP and RFI responses end to end, from requirement matrix and compliance mapping through win themes, solution narrative, references and pricing story, to a submission that lands on time.
- Write the PRD and functional specification the engineering team builds from, at a level of detail that removes ambiguity rather than passing it downstream.
- Build demo-grade prototypes yourself using AI tooling, with the scripted flow and talk track that makes a client believe the thing before it exists.
- Redesign the workflow around the solution, and lead the change management, adoption and training that decides whether any of it gets used.
- Run the engagement: scope, plan, sequence, govern, escalate, manage the steering committee, and hold the commercial line on scope and margin when the client would prefer that you did not.
- Track realised value against the case you signed up to after go-live, and close the gap or explain it. This is where you find out whether the business case was real.
- Carry the client relationship at CXO level, and turn a delivered engagement into the next one.
Qualifications
An MBA from a leading programme is the common route into this role, not the only one. An equivalent track record built through strategy consulting, Big Four advisory, or product and programme management at a product or technology company carries the same weight. We are more interested in what you have owned than where you studied.
Three to seven years of total experience including pre-MBA, with clear evidence of owning work end to end rather than contributing to someone else's engagement.
Required Skills
- Structured problem-solving and diagnosis. Break an ill-defined commercial problem into a hypothesis you can test with the data actually available, not the data you wish existed.
- AI opportunity and ROI judgement. Tell the difference between an AI use case that moves a P&L line and one that demos well, and be willing to say so before the client has fallen in love with it.
- Business case construction and defence. Build a case from a measured baseline, then hold it under CFO-grade challenge on assumptions, attribution and timing.
- Proposal and commercial craft. Own an RFP response end to end and land it on time, including the pricing story and the parts nobody wants to write.
- Product and delivery execution. Specify what gets built well enough that engineering does not have to guess, then run the engagement to the plan you set.
- AI-native working. Build your own prototypes and use AI tooling as the default across research, modelling and drafting, with accountability for verifying what it produces rather than shipping it unread.
- Executive communication and client leadership. Hold a room at CXO level, deliver bad news early, and hold the commercial line on scope and margin while the relationship survives it.
- Ownership under ambiguity. What you did when the brief contradicted itself, the sponsor changed, and nobody was coming to help.
Preferred Skills
- Sector depth in financial services, insurance, telecom, airlines, retail or industrials, and familiarity with the operating and cost structures that come with them.
- Strong Excel modelling: driver-based cases, sensitivity and scenario analysis built to be audited by someone else.
- Technical literacy sufficient to hold a credible conversation with engineers on feasibility, data readiness, integration effort and where the estimate is soft.
- Experience with outside-in commercial assessment where client data access is limited or comes late. You will be trained on Aistra's own accelerators, including First Cut and the Aistra deck system, so familiarity with the method matters more than the tool.
- Workflow redesign and change management on programmes where adoption, not build, was the binding constraint.
- Comfort operating inside enterprise procurement and security processes, including client NDAs and the data-protection regimes that apply.
- Willingness to travel and work on client sites as engagements require.
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