Top Artificial Intelligence Jobs in Bengaluru

Design, build, and own automated GTM workflows and campaign pipelines; create and configure AI agents and internal self-serve tools; maintain funnel and pipeline data accuracy; instrument end-to-end reporting; and partner with sales, marketing, and leadership to turn GTM strategy into reliable, scalable systems.

The AI Engineer will build and optimize an enterprise search solution, manage a knowledge graph, develop ranking models, and enhance search relevance.

Lead global quality engineering and testing practices for AI-driven SaaS products, enhance automation, and ensure high-quality releases through effective strategies and collaboration.

Lead product quality across the SDLC by reducing defects, driving root-cause analysis, defining automation strategy and quality gates, building automated test frameworks (Playwright, API, integration, performance), integrating tests into CI/CD, enforcing release readiness, and using Claude Code and other AI tools to analyze issues and improve engineering outcomes.

The Lead Automation Engineer will develop and maintain automated testing frameworks for network observability, enhance product quality, and collaborate with engineering teams to improve testing strategies and practices.

Build data integrations and tooling that combine CRM, product telemetry, support, billing, and other signals to provide GTM teams with context, automation, and real-time augmentation. Enable account prioritization, allocation, and funnel conversion tracking to increase revenue and save time across sales, marketing, growth, and customer success.

Work on a TypeScript full‑stack product (Next.js/React) with an AI pipeline using Anthropic Claude, real‑time collaboration (Liveblocks/Yjs/Tiptap), and Cloud Run background jobs. Build UI features, improve AI agent prompts/schemas/output rendering, write and maintain unit tests, read docs to unblock yourself, and grow to own product slices.

Lead architecture and implementation of scalable, distributed enterprise features across multi-cloud environments. Own full lifecycle from whiteboarding and design to coding, integrations, and post-launch stability. Build agent-driven workflows that connect autonomous AI agents to APIs and data pipelines. Execute as a hands-on individual contributor, leveraging AI tools to accelerate delivery while ensuring secure, observable, and extensible enterprise integrations.

Design and implement AI-enabled ServiceNow solutions across ITSM, FSM, and ITAM. Provide technical leadership and ensure best practices in AI capabilities, facilitate stakeholder workshops, and guide project teams.

Design and presales of end-to-end AI/HPC infrastructure: size GPU clusters, storage, networking, Kubernetes/container platforms, integrate liquid-cooled racks with facility constraints, validate solutions with OEMs, and support delivery for scalable, operable AI deployments.