Solution Engineer (AI & Automation)

Confirmed live in the last 24 hours

Boku

Mumbai

On-site

Posted March 26, 2026

Job Description

Boku Inc. (BOKU.L) is the leading global provider of local mobile-first payments solutions. Global brands including Amazon, DAZN, Meta, Google, Microsoft, Netflix, Sony, Spotify, and Tencent rely on Boku to reach millions of new paying consumers who do not use credit cards with our purpose-built payment network of more than 300 local payment methods across 70+ countries. Every year, Boku processes over $10 billion in value for our customers. Incorporated in 2008, Boku is headquartered in London and San Francisco and has employees in over 39 countries around the world, including Brazil, China, Estonia, Germany, Ireland, Japan, Singapore, and the UAE. Boku is a truly global company that takes pride in its diversity and thriving equal opportunity workplace.

Role Purpose

Boku is building a next-generation enterprise automation and AI platform to serve the whole organisation. This platform combines an AI-native agent and chat layer with a dedicated workflow automation capability, delivered as a shared Automation-as-a-Service (AaaS) model across Global IT and the wider business. The Solution Engineer is a hands-on technical role responsible for designing and delivering the platform and the automation and integration solutions built on and around it. The role spans full-stack engineering - from backend integration and agent configuration through to frontend tooling — and requires the ability to translate real business problems into scoped, well-architected automation solutions. This is a senior individual contributor role that demands autonomy, critical thinking, and clear ownership of delivery.

Key Responsibilities

Design and deliver the AaaS platform alongside automation and integration solutions that support business and IT processes, working across both the core platform and solutions built on top of it.
Translate cross-functional business problems into scoped automation use cases — defining inputs, outputs, required tools, decision points, and appropriate human confirmation gates.
Contribute to the development and evolution of the AaaS capability, including reusable components, integration patterns, and shared standards.
Work with stakeholders across IT and the business to identify automation opportunities and gather clear requirements.
Build, test, deploy, and support automation and integration solutions to a production-ready standard.
Design, configure, and orchestrate AI agent behaviours — including tool scoping, skill composition, guardrail design, and agent orchestration — in line with platform architecture and governance requirements.
Create and maintain technical documentation, runbooks, and solution design artefacts.
Apply AI and intelligent automation where it adds clear, demonstrable value — and advise stakeholders honestly on where it does not.
Collaborate with Global IT teams to ensure solutions meet security, compliance, and operational requirements.

Skills & Experience

Required

Hands-on experience designing and building automation and integration solutions in real-world enterprise environments.
Strong working knowledge of TypeScript and Python; comfortable with SQL for querying and schema understanding.
Frontend development experience with React, including building functional interfaces and understanding of SSO / MSAL authentication flows.
Practical experience with Azure-native services, including serverless compute, Azure App Service, Azure SQL, and Entra ID / RBAC.
Strong understanding of REST API design, OAuth 2.0, webhooks, and enterprise SaaS integration patterns.
Experience integrating with enterprise platforms across service delivery, HR, finance, sales, marketing, and collaboration functions (e.g. ITSM tooling, ERP, Microsoft 365 / Graph).
Understanding of LLM orchestration, agent framework composition, tool call design, and agent orchestration across enterprise AI platforms — including experience with API-based and cloud-hosted model providers.
Familiarity with MCP (Model Context Protocol), A2A patterns, and other emerging agent integration standards.
Experience with RAG pipeline design, prompt engineering, and applying AI in constrained, governed environments.
Ability to scope automation use cases