Forward Deployed Engineer

Most engineers ship features. You'll ship outcomes, directly in the hands of customers, on live systems, where it actually counts. And you'll do it faster than anyone thought possible.

The Company

Sendbird is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations—chat, voice, video, messaging APIs—and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users.

We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good.

We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack—into intelligence, into experience, into outcomes.

We had a choice: protect what we built, or reinvent ourselves.

We chose reinvention.

In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX—built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to Delight.ai.

The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost—the feeling of being truly understood and cared for. Not satisfied. Delighted.

The Product

Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel—chat, SMS, email, voice, WhatsApp—without losing the thread. We're building AI that makes customers feel understood, seen, and remembered.

Why Forward Deployed Engineer

AI agents don't fail in demos. They fail in production, when the edge case hits, the prompt breaks, or the integration misbehaves in front of a real customer. That gap between "it works in the sandbox" and "it works in the wild" is exactly where this role lives.

We're deploying AI agents for some of the world's biggest brands. Each one has unique workflows, data, and stakes. We need engineers who can sit across from a customer, understand the problem, and build the solution fast, not hand off a spec and wait. If you treat AI as a core part of your toolkit and not an afterthought, you'll move at the speed this role demands.

The Role

You'll own the full technical lifecycle of customer AI agent deployments, from first integration to live monitoring, working at the intersection of product, engineering, and customer outcomes. This role is for engineers who use AI to compress timelines, ship higher-quality work, and want their impact felt immediately, not six months from now.

You might be this person if:

• You think in systems — inputs, outputs, failure modes — and you naturally ask "what happens when this breaks?" before anyone else does
• You've debugged something live, under pressure, with a customer watching, and you didn't flinch
• You use AI tools daily to prototype, debug, and iterate, and you've figured out how to get 10x the output without cutting corners on quality
• You read a system prompt the way a compiler reads code, spotting logic gaps, unintended behaviors, and edge cases others miss
• You've built something end-to-end, frontend to backend to deployment, and you're proud of how it actually held up
• You learn fastest by building, not by reading docs, and you've shipped something with a new API within days of touching it for the first time
• You care about what the customer actually experiences, not just whether the tests pass
• Ambiguity doesn't slow you down. You'd rather build a rough solution and iterate than wait for a perfect brief

You need to have:

• 2-3 years of hands-on software engineering experience in full-stack or backend development
• Strong Python proficiency and the ability to write clean, maintainable code under real-world constraints
• Practical experience with React and modern JavaScript/TypeScript on the frontend, plus backend frameworks like Node.js, Django, or Express
• Hands-on experience with LLM APIs (e.g., OpenAI, Claude) or agent frameworks such as LangChain
• Familiarity with RAG pipelines, knowledge base integration, and cloud deployment platforms (e.g., AWS Lambda, Vercel, GCP Cloud Functions)

What you'll actually do:

• Deploy production-grade AI agents tailored to each customer's environment, owning setup, configuration, and go-live
• Tune system prompts and agent behaviors against real-world use cases, using AI-assisted workflows to move from hypothesis to working solution faster than a traditional dev cycle allows
• Prototype and ship fast, leveraging agentic coding tools to build agent interfaces, dashboards, and backend integrations with Next.js, React, and modern APIs
• Integrate RAG pipelines and knowledge bases that give agents the context they need to perform
• Monitor live deployments with logging, metrics, and observability so issues surface before customers notice them
• Collaborate with Forward Deployed PMs, core product, and design to turn customer needs into working solutions, often building a prototype before the meeting ends
• Lead technical demos, document implementation decisions, and maintain architecture diagrams that actually reflect reality

Added Value

• Prior experience tuning or debugging AI agent performance in live, production environments
• Background in 0-to-1 builds, customer-facing implementation, or technical consulting, with a track record of navigating the messiness of real deployments

What We Offer Includes (but is not limited to)

• 20 days PTO, 13 paid US company holidays, 7 sick days, 1 volunteer day, plus 2 rest/rejuvenation and birthday days off
• Company subsidized medical, dental, vision insurance
• Flexible spending accounts
• Parental leave
• Life and disability insurance
• Be Your Best Self: An annual stipend of $3,500 (prorated after 3 months) for expenses ranging from professional development classes and training, to personality assessments, gym memberships, books, fitness classes, mental health services, and massages

Pay Transparency

For cash compensation, we set standard ranges for all roles based on function, level, and geographic location.  To determine our ranges, we utilize a variety of compensation data benchmarked against similar-stage growth companies.   A reasonable estimate of the current salary range for this role is $150,000 - $180,000 .  This range is specific to the San Francisco Bay market.  We consider several factors when making final compensation decisions including, but not limited to, skill sets, experience and training, licensure and certifications, and other business and organizational needs which may cause your specific offer to vary from the amount listed above.

Flexible Work Policy

We offer a flexible work schedule at Sendbird.  We also value collaboration and relationship building.  With those values in mind, we require all employees within an hour's commute range of their local office to gather with their team in the office three days per week as a minimum.  Some of our roles require a more frequent in-office schedule.  Please work with your manager to understand the office time requirements for your position.

What diversity and inclusion mean to us

There is no such thing as a perfect candidate and the best employees come from a wide range of backgrounds, experiences, and skill sets. Sendbird is a place where everyone can learn and grow. We respect, promote, and encourage diversity for equal employment opportunities and encourage you to apply if this role excites you.

Why Sendbird

We're not iterating on an existing product. We're building a new category, AI that genuinely delights customers, on top of infrastructure that's already at enterprise scale. This role puts you at the center of that: real customers, real deployments, real impact. If you want to own outcomes and help define what forward-deployed AI engineering looks like, this is the place.