AI Enablement Engineer

The Opportunity

Keyloop is in the middle of an AI-enabled transformation, driven by the AI Empowered Programme — a board-mandated effort to lift AI maturity across our ~80 Product & Engineering teams. Two teams sit at the heart of it: Keystone, which builds the underlying AI capability and technical pathways, and Impost, which enables teams to adopt that capability hands-on.

We're looking for an highly motivated AI Enablement Engineer to join Impost and help our engineering teams put Keystone's AI capability to real, effective use. The primary mode of engagement is through a team's AI Champion — coaching, mentoring, or pairing with them to drive sustained, long-term change. You'll also work directly with teams for shorter periods to help resolve specific technical challenges, or gain the kind of deep, first-hand insight that's only visible from inside a team's day-to-day work and feeding it back into the programme.

This is a hands-on software engineering role, not an "engineer who used to code." You'll sit on the frontline of AI-driven development lifecycle innovation at Keyloop — as part of the Impost team, you'll be the first adopter team for Keystone's experimental new solutions, taking ownership of real internal systems as genuine test grounds. You'll contribute directly to Keystone's solutions — sometimes through early feedback on what's rough or missing, sometimes through hands-on contribution and pull requests.

Keyloop itself is a dual-speed technology organization: a large, successful DMS heritage business running on established platforms built up over decades, alongside Fusion — a modern, cloud-native Automotive Retail Platform built on AWS, event-driven domain services. You won't need to master every technology across that estate yourself — each team owns its own stack, and that expertise stays with them. Your focus is AI: helping teams leverage Claude Code, skills, agents, and Keystone's recommended solutions effectively, whatever stack they happen to be working in.

Must-have:

• Fluency in AI assisted and agentic software development

• Strong, hands-on engineering background with genuine credibility pairing and mentoring other engineers on real technical problems.

• Comfort mastering new, evolving AI capability early — often ahead of formal documentation or a fixed playbook.

• A genuine interest in, and demonstrated ability to have a strong positive impact on the growth of others — through pairing, mentoring, coaching, or developer advocacy. This role is built around lifting other people up, not working heads-down in isolation; if that's not energizing to you, this isn't the right fit.

• Ability to read a team's context and choose the right mode of engagement (direct vs. through a Champion) rather than applying one approach everywhere.

• Experience working effectively across a distributed, multi-location engineering organisation.

• Based in, or willing to work from, Hyderabad (India).

• Direct & Champion-Mediated Enablement: Provide hands-on technical support, training, and mentoring on Keystone's AI capability — working directly with a team or through its AI Champion, depending on context and champion maturity.

• Champion Development: Build the technical capability of AI Champions so they can scale enablement within their own teams, multiplying Impost's reach beyond what a small central team could do alone.

• Early Adoption ("Dogfooding"): Take ownership of real internal systems — as the test ground for Keystone's experimental new solutions before they reach any other team. Build with them, break them, and feed what you learn directly back into Keystone's own development, through early feedback or, where appropriate, hands-on contribution and pull requests.

• Field Feedback & Cross-Pollination: Surface what works and what doesn't from real engagements; escalate unresolved technical friction to Keystone; spot effective practices in one team and help spread them to others.

• Triage: Recognise when a team's blocker isn't a technical/AI problem, and surface it to the Enablement Workstream for routing — rather than trying to solve it yourself.

• Community & Advocacy: Stay active in relevant AI communities of practice and forums as a natural part of the job; contribute technical content, demos, or talks as capacity allows.

• AI Landscape & Continuous Learning 
  Proactively track developments in AI tooling and practices internally and externally. Bring relevant insights into the organisation and translate them into actionable enablement opportunities before they are asked for.