Technical Support & Solutions Associate - Platform-as-a-Service (PaaS)

Karya’s mission is to leverage the AI revolution to create dignified earning and learning opportunities for low-income communities across the world. In India, our smartphone-based digital work platform has enabled over 120,000 people to build language datasets and evaluate AI models while earning fair wages. With pilots in Kenya and Ethiopia and partnerships with leading AI labs, we are advancing language technologies for underrepresented communities. By combining dignified digital work with frontier AI innovation, Karya hopes to build a new AI economy that is equitable, inclusive, and community driven.

Karya's PaaS vertical is the organization's global expansion arm, taking Karya's ethical data collection infrastructure to partners across Africa, Southeast Asia, and Latin America, deployed locally. This is one of Karya's largest bets: we're moving from a set of internally-run deployments toward a self-serve platform that partners can configure and operate themselves.

We're looking for someone to be the first line of defence on that front: triaging and resolving partner-facing technical issues, coordinating with engineering when something needs a real fix, and  critically - spotting the patterns behind repeat issues and scoping them as automation opportunities the platform team can build against. This role is explicitly built to evolve. As the platform gets more self-serve, the volume of manual triage should shrink and the expectation is that you grow with it, moving from first-line support toward solutions architecture: designing how partners configure and deploy the platform themselves, rather than fixing things alone. 

• →First-line technical support. Own initial triage for partner-facing technical issues — diagnose what's broken, resolve what you can directly, and route what you can't to engineering with enough context that it doesn't bounce back.
• →Scope automation opportunities. Spot the pattern behind repeat issues and turn it into a scoped opportunity for the product team — what's repetitive, roughly what it would take to fix at the platform level, and what it would save.
• →Client-facing communication. Talk to partners directly during issues — translating technical problems into plain language without underselling the problem or overwhelming a non-technical partner contact.
• →Internal coordination. Sit between partners and engineers — chasing fixes, setting expectations on both sides, and making sure at-risk timelines are flagged on time.
• →Read and modify code. Debug issues, make small fixes or configuration changes yourself where possible, and write precise, actionable bug reports for engineering when you can't.
• →Grow into solutions architecture. As the platform becomes more self-serve, take on more of the deployment-design and configuration-architecture work that reduces the need for manual triage in the first place.

Experience: ~1–3 years, with:

• • Tech stack: Python and Node.js 
  • Comfort reading and modifying code — you don't need to be a full-time engineer, but you should be able to debug real issues and make small fixes, not just describe them
  • Exposure to client-facing or partner-facing work — this role talks to real partners during real problems, often ones who aren't technical themselves
  • Great communication skills to translate complex problems into understandable issues and solutions
  • Enough technical grounding to eventually take on solutions-architecture work — understanding of APIs, deployment models, and configuration-driven systems will matter more over time, not less
  • Ability to handle pressure; partners come to this role when something's already broken
  • A pattern-recognition instinct — the automation-scoping half of this job depends on noticing what's repetitive, not just closing tickets
  • Comfort with a role that's designed to change — this isn't a fixed job description forever; the expectation is that both the work and the person's scope shift as the platform matures
  • Genuine interest in Karya's mission — ethical data work, fair compensation for data workers, and community ownership of data are core considerations, not side context