Cvent is a leading meetings, events, and hospitality technology provider with more than 6,000+ employees and 34,000+ customers worldwide, including 60% of the Fortune 500. Founded in 1999, Cvent delivers a comprehensive event marketing and management platform for marketers and event professionals and offers software solutions to hotels, special event venues and destinations to help them grow their group/MICE and corporate travel business. Cvent's strength lies in its people, fostering a culture where everyone is encouraged to think like entrepreneurs, taking risks and making decisions confidently. AI at Cvent: Leading the Future
Are you ready to shape the future of work at the intersection of human expertise and AI innovation At Cvent, we're committed to continuous learning and adaptation—AI isn't just a tool for us, it's part of our DNA. If you love to experiment boldly, share your discoveries, and help define best practices for AI-augmented work, you'll thrive here. Our team values professionals who thoughtfully integrate AI into their daily work, delivering exceptional results while relying on the human judgment and creativity that drive real innovation.

Throughout our interview process, you'll have the chance to demonstrate how you use AI to learn, iterate, and amplify your impact. If you're excited to be part of a team that's leading the way in AI-powered collaboration, we'd love to meet you.
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Bengaluru, India | Team: Splash | Reports to: Software Engineering Manager, Splash

We are standing up a current engineering team in Bengaluru with a single charter: build the AI-powered features that will define the next generation of Splash. The team works as a peer to the established Splash engineering and product teams in Bangalore, North America, and Spain, who own adjacent parts of the platform and with whom we plan, design, and ship. This is an AI-first team in two senses: we ship AI into the product, and we build software with AI — agentic coding tools, spec-driven development, and disciplined review of AI-generated output are the default way of working here, not an experiment.

We are looking for Senior Software Engineers to build Splash's next generation of AI features across the full stack — Java and Spring Boot services on AWS that orchestrate LLM calls, retrieval, and tool use, and React and Next.js front ends that turn them into experiences users trust. You have taken LLM-powered functionality to production, not just prototypes, and you are comfortable owning a feature from the API contract and model integration through to the interface. You may lean towards the backend or the front end,



but you are credible across both and willing to work wherever the feature needs you. You take ownership from design to deployment, thrive in ambiguity, hold yourself to a high standard, and already build with agentic coding tools as a matter of course — and you are rigorous about verifying what they produce. Build and ship AI features for Splash
Design and deliver AI features end to end: Java and Spring Boot microservices on AWS that orchestrate LLM calls, retrieval, tool use, and structured generation; and React and Next.js front ends with TypeScript — conversational and agentic interfaces, streaming responses, human-in-the-loop review flows, and generative tools embedded in existing Splash workflows.
Build the AI platform plumbing that features depend on: prompt and model versioning, evaluation harnesses, guardrails, caching, cost and latency controls, and observability for LLM calls.
Work with relational and NoSQL data stores, vector search, and event-driven messaging (e.g. SQS, SNS, Kafka) to build reliable, scalable data flows for AI workloads.
Make AI experiences trustworthy and usable: handle latency, uncertainty, errors, and model failure modes gracefully in the interface; and instrument what you ship so we can measure how users actually use it.
Own features end to end — from design and development through deployment, monitoring, and production support — with minimal oversight.

Own quality and non-functional requirements
Ensure what you ship meets Splash's bar for security, scalability, resiliency, accessibility, performance, and responsible-AI expectations, including evaluation of model output quality before and after release and how that output is presented and controlled in the UI.
Write meaningful unit, component, integration, and end-to-end tests and evals; and raise the quality of the code base you touch.

Work AI-natively
Work AI-natively every day: write specs that an agent such as Claude Code, OpenAI Codex, or GitHub Copilot agents can execute, delegate well-bounded work to it, and review and correct its output with the same rigour you would apply to a colleague's pull request.
Know where AI tooling fails. Verify generated code, tests, and documentation for correctness, security, and maintainability before it ships, and share what you learn about effective prompting, context, and verification with the team.

Write design notes, decisions, and status updates that colleagues in other time zones can act on without a meeting, and share on-call and production support for the services and applications your team owns.

5+ years of professional software development experience building and operating production web applications across the stack.





- Strong expertise in Java and Spring Boot for building distributed microservices — service decomposition, inter-service communication (REST and messaging), and resilience patterns.
- Strong expertise in React and Next.js with TypeScript — component architecture, state and data-fetching patterns, server-side rendering, performance optimisation, and accessibility. Hands-on experience building and operating services on AWS (e.g. ECS/EKS or Lambda, SQS/SNS, RDS or DynamoDB, S3, CloudFront) and with cloud-native architectures.
- Experience designing and consuming GraphQL and REST APIs, and with relational and NoSQL databases, including schema design and query performance.
- Experience building AI-driven user experiences: streaming LLM output, conversational or agentic UI patterns, and handling latency and uncertainty in the interface.
- Hands-on fluency with AI-assisted and agentic software development — you use tools such as Claude Code, OpenAI Codex, or GitHub Copilot agents in your own work: writing specs an agent can execute, reviewing and correcting its output, and knowing where these tools fail. This must be lived experience, not familiarity with the concepts.
- Experience shipping AI-driven functionality to production — LLM-powered features such as retrieval-augmented generation, agents, or structured generation — and a working understanding of evaluation, prompt and model lifecycle, cost, latency, and failure modes.
- Strong software engineering fundamentals: data structures, software design principles, distributed systems, and a track record of owning non-functional requirements (security, scalability, resiliency, performance) for production systems.
- Experience with CI/CD pipelines, containerisation, and running services you built in production.
- Clear written and verbal communication in English, and the ability to work as a peer with engineering, product, and design colleagues in other regions and time zones.
- Bachelor's degree in Computer Science or a related technical discipline, or equivalent practical experience.

Experience with vector databases and retrieval pipelines (e.g. OpenSearch, pgvector, Pinecone) and with embedding and chunking strategies.
Experience with LLM orchestration frameworks and protocols (e.g. Spring AI, LangChain4j, Vercel AI SDK, Model Context Protocol) and with multiple model providers (Anthropic, OpenAI, AWS Bedrock).
Experience with design systems and component libraries at scale, and with product analytics and experimentation tooling.
Experience with Kubernetes, Docker, or Terraform, and with observability tooling such as Datadog (including RUM and front-end performance monitoring).
Experience building evaluation frameworks or observability for LLM features in production (e.g. offline eval sets, LLM-as-judge, tracing with Datadog or LangSmith).
Experience with GraphQL APIs, including schema design and federation.
Experience in event, marketing, or martech products, or other B2B SaaS with high-volume customer-facing workflows.
Experience joining a newly formed team and helping to establish its norms, tooling, and ways of working.

📌 Senior Software Development Engineer, Full Stack (Bengaluru)
🏢 Cvent
📍 Bengaluru