realfast is India's first post-AI IT services company, built from scratch around one metric: how quickly a signed contract becomes working software a client is paying for. Founded by the team that scaled Gojek and backed by Peak XV Partners (formerly Sequoia India & SEA) and RTP Global.
Our platform, Exo, powers the entire delivery operation. It ingests client documentation, codebases, and requirements within hours, compressing weeks of traditional discovery into days, then works alongside our teams to deliver production-ready solutions. We've delivered production-ready solutions in days that traditionally take months. The methodology behind this is Real Agile, built specifically for how IT services works in the AI era.
We hire for judgment, because everything that doesn't require it is already automated. What's left is the job.
Here's what we're looking forSomeone who can walk into a client organisation, diagnose where work breaks down, and identify the one workflow where AI will deliver the fastest, most credible business impact. You'll be the spine of client engagements — bridging business stakeholders and our engineering team, owning the delivery narrative, and ensuring AI gets embedded in how work actually gets done, not bolted alongside it.
This is an AI-native role. You don't just advise clients on AI — you use it yourself, every day. You bring AI into how you run discovery, build business cases, structure communications, and accelerate delivery. If AI isn't already part of how you work, this role isn't the right fit.
What you'll doDiscovery
Facilitate workshops with client stakeholders to surface operational friction
Map current-state workflows with enough precision to support a business case
Classify work breakdown into Automate, Augment, or Connect categories
Run sweet spot analysis — finding the intersection of business metrics, repeatable workflows, and existing data
Build evidence-based ROI frameworks grounded in real workflows, not assumptions
Define engagement scope: one workflow, one business metric, one delivery horizon
During Delivery
Serve as the day-to-day client point of contact
Translate between client business language and the technical delivery team
Manage stakeholder communications and progress narratives
Hold scope boundaries against client requests
Coordinate before/after business impact measurement
Prepare end users for adoption — ensuring AI embeds in workflows, not bolts on
Closing & Expansion
Drive documentation and handover coordination
Identify and frame the expansion path for the next phase
Brief the senior partner on account development opportunities
3–5 years of experience in management consulting, implementation consulting, business analysis, or client-facing enterprise delivery roles
Proven ability to run structured discovery and map business processes
Track record of delivering defined outcomes, not just ongoing BAU work
Quantitative comfort — building ROI models and business cases from evidence
Technical literacy sufficient to have credible conversations with engineers about AI, data, and system integration
Clear written and verbal communication across operational and senior stakeholder audiences
Self-starter who can structure ambiguous situations without heavy direction
Active AI practitioner — you use AI tools in your daily work and have strong opinions on where they add value and where they don't
Management consulting (Big 4, boutique digital/AI/strategy firms)
Implementation consulting (Salesforce, SAP, Workday, ServiceNow)
Business analysis on enterprise technology programmes
Solutions consulting or pre-sales at B2B SaaS companies
Product management at enterprise software companies
Strategy or operations roles where you redesigned processes with measurable outcomes
You're frustrated when AI projects never escape demo mode
You can walk into an operations manager's office, understand their pain in 30 minutes, and leave with a clear problem statement
You think in workflows and outcomes, not features and tools
You're as comfortable at a whiteboard as with a slide deck
You want to see the work you scoped actually deployed and measured
You need extended discovery phases before making a recommendation
You prefer internal analysis to client conversations
You think AI strategy is about picking the right model, not redesigning the workflow
You measure success by the quality of your slide deck, not the business metric it moved
You need a stable, predictable scope to be effective
You treat AI as something to advise clients on rather than something you use yourself
