Lead Software Engineer (Full Stack)

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. Our technology brings millions of people together at events around the world. In short, we're transforming the meetings and events industry through innovative technology that powers human connection.

Headquartered in Tysons Corner, Virginia, Cvent (formerly NYSE: CVT) was acquired by Blackstone and Vista for $4.6B in 2023.

Cvent's strength lies in its people, fostering a culture where everyone is encouraged to think like entrepreneurs, taking risks and making decisions confidently. We value diverse perspectives and celebrate differences, working together with colleagues and clients to build strong connections.

Cvent is redefining the meetings and events industry through technology that advances human connection.

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. We're looking for candidates who are eager to evolve alongside technology. 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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About the role:

Location: Bengaluru, India | Team: Splash | Reports to: Software Engineering Manager, Splash

Splash is Cvent's event marketing platform. We are standing up a new 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 a Lead Software Engineer to lead the design and delivery of AI features across the Splash stack — Java and Spring Boot services on AWS and React and Next.js front ends — and to set the engineering bar for a newly formed team. You have 8+ years of hands-on experience, you have taken LLM-powered functionality to production and owned its quality, and you can zoom out to shape architecture and zoom in to deliver production-ready code. You will lead design for multi-engineer work, mentor the Senior Engineers on the team, and partner with the Engineering Manager and Principal Engineer on how the team works — including how agentic coding tools and spec-driven development are used, reviewed, and measured. You thrive in ambiguity, take end-to-end ownership, and hold the people around you to a high standard without lowering your own.

In This Role, You Will:

Lead delivery of AI features for Splash

• Lead the end-to-end design and delivery of full-stack AI features — from problem framing with Product and Design through architecture, implementation, evaluation, release, and operation — for a product area owned by the team.
• Drive architectural decisions across the team's Java and Spring Boot microservices, event-driven integrations on AWS, GraphQL APIs, and React and Next.js front ends, so that they form a cohesive, maintainable platform for AI features.
• Design the AI components of features — retrieval, agent and tool-use patterns, structured generation, prompt and model lifecycle — with explicit attention to evaluation, cost, latency, and failure modes.
• Break ambiguous requirements into clear, sequenced engineering plans; coordinate dependencies with Splash teams in other regions; and communicate progress and trade-offs to stakeholders honestly.

Set the engineering bar

• Be a quality gate for the team: review designs, AI-generated code, tests, and evaluations for correctness, security, scalability, and maintainability, and teach the Senior Engineers to do the same.
• Own non-functional requirements — security, scalability, resiliency, accessibility, performance — and responsible-AI expectations for what the team ships.
• Lead incident response and post-incident learning for the team's services, and drive the improvements that come out of it.

Lead the AI-native way of working

• Together with the Engineering Manager, define how the team works with agentic coding tools and spec-driven development: what a good spec looks like, when to delegate to an agent, and what must be verified by a human.
• Model that way of working in your own code and reviews, keep the team's tooling and practices current as the AI development landscape changes, and share what works with the wider Splash organisation.

Grow people

• Mentor and technically guide engineers on the team through pairing, design reviews, and direct, timely feedback, elevating code quality and design thinking.
• Contribute to hiring: interview candidates, help calibrate the bar, and help new engineers become productive quickly.

Here's What You Need:

Primary Skills:

• 8+ years of professional software development experience, including leading the design and delivery of significant features or systems with other engineers.
• Strong expertise in Java and Spring Boot for distributed microservices, and strong experience with React or Next.js with TypeScript — you are credible and hands-on across the full stack.
• Experience designing and operating event-driven microservices on AWS (e.g. ECS/EKS, Lambda, SQS/SNS, EventBridge, RDS or DynamoDB) and with GraphQL and REST API design.
• Experience with relational and NoSQL databases, including schema design and performance tuning.
• 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 taking AI-driven functionality to production and owning its quality — LLM-powered features such as retrieval, agents, or structured generation — including evaluation, prompt and model lifecycle, cost, latency, and failure modes.
• Strong engineering judgment: you can evaluate a design or a change for correctness, security, scalability, and maintainability without having written it yourself, and you have a track record of owning non-functional requirements for production systems.
• Experience mentoring engineers and leading technical work across a team.
• 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.

Preferred Skills:

• 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 vector search and retrieval pipelines (e.g. OpenSearch, pgvector) in production.
• Experience with Kubernetes, Docker, or Terraform, and with observability tooling such as Datadog.
• 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.