PROGRAMMING - UNREAL ENGINE

What We Do

Unreal-powered projects have been on the bleeding edge of real-time entertainment for over 20 years. Our team of programming experts are always innovating to improve the tools and technology that empower content developers worldwide.

What You'll Do

As a Principal Software Programmer of the Media Services team, you'll take full ownership of the platform powering real-time communication across the Epic Games ecosystem. You'll help set the technical direction for Epic's WebRTC-based products and implement features from design through final delivery.

In this role, you will

• Work on the WebRTC integration across different Epic Games teams, design and hands-on implementation of new features
• Design, develop, and continuously improve our WebRTC client and server stack across platforms 
• Investigate and evaluate new technologies to drive innovation in real-time communication services
• Drive timelines, resolve technical blockers, and deliver with a high degree of autonomy

What we're looking for

• Highly proficient in C++, with a strong command of performance-critical systems
• Deep understanding of WebRTC signalling concepts, protocols, and architecture
• Proven experience in debugging and optimizing WebRTC stacks at scale
• Experience designing and maintaining C APIs for broad platform distribution
• Familiarity with build systems like GN and Ninja
• Demonstrated ability to independently own and deliver complex, long-horizon programming projects
• Strong communication with a track record of cross-team alignment and technical decision-making
• Leadership experience is a plus

EPIC JOB + EPIC BENEFITS = EPIC LIFE

We pay 100% for benefits for both employees and dependents and offer coverage for supplemental medical, dental, vision, critical illness, telemedicine, Life and AD&D, long term disability insurance as well as weekly indemnity (short term disability) and a retirement savings plan with a competitive employer match. In addition to the EAP (employee assistance program), we also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents.

Pay Transparency Information

The expected annual base pay range(s) for this position are detailed below. Each base pay range is relevant only for individuals who are residents of or will be expected to work within the specified locale. Compensation varies based on a variety of factors, which include (but aren’t limited to) things such as skills and competencies, qualifications, knowledge, and experience. In addition to base pay, most employees are eligible to participate in Epic’s generous benefit plans and discretionary incentive programs (subject to the terms of those plans or programs).

Your role
As a Sr. Software Engineer on the Tel Core team, you are the steward of our media engine’s evolution. You will bridge the gap between high-level product goals and technical execution, ensuring our telephony stack remains resilient as we scale. You’ll mentor peers and shape the long-term roadmap while fostering a culture of engineering excellence. Your success is defined by the seamless, high-quality audio experience of millions of users.

This position reports to an Engineering Manager in the Telephony Core team and has the opportunity to be based in either Vancouver or Kitchener, Canada locations 

We don’t mind if you come from a different engineering background or haven’t worked in real-time media before. Just be excited to learn, to contribute to the team, and to build a fast, reliable, elegant product that delights our customers.

What you’ll do

• Maintain and modernize the real-time services that run on the Telephony Engines. Architect backend libraries and APIs to integrate with the broader Telephony Platform.
• Build and optimize low-latency media pipelines for voice and video—tuning codecs, RTP flows, and congestion-control behavior to deliver consistently clear conversations over unreliable networks.
• Investigate and resolve complex production issues across PSTN, WebRTC, and carrier boundaries using Telephony Engine logs, PCAPs, observability tools, and data-driven experimentation.
• Run load, failover, and regression tests on Telephony Engines and backend services to validate scalability, resilience, and capacity limits
• Partner with Tel Cloud, Tel Edge, Calling, and AI teams to design end-to-end call flows and integrations
• Participate in on-call and release rotations, owning Terraform- and GKE-backed rollouts, monitoring health, and driving follow-ups that continuously make the platform safer and easier to operate.
• Shape the Tel Core roadmap by turning broad epics into clear designs and mentoring other engineers.

Skills you’ll bring 

• Bachelor's degree in Computer Science or equivalent practical experience.
• 5+ years of software engineering experience, including owning substantial production backend systems in a SaaS or real‑time communications environment.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Deep expertise in C/C++ and Python.
• Experience with (or strong interest in learning) SIP, WebRTC, RTP/RTCP, DTLS/SRTP, and media codec negotiation in a production setting.
• Experience troubleshooting and improving real‑time media quality (e.g., jitter, packet loss, choppy audio, codec issues) is a strong plus.
• Comfortable working on KTLO (bugs, refactors, upgrades) as well as strategic roadmap items, and using data to prioritize impact.
• A deep understanding of reliability engineering, including the ability to build observability into services, eliminate performance bottlenecks, and manage the lifecycle of safe software releases.
• A strong sense of urgency, personal agency, and customer empathy.
• Passion for data driven decisions, building resilient systems, and solving classes of problems.

Our tech stack

• C, C++, Python, Go, Lua.
• Kubernetes, Redis, ElasticSearch, BigQuery.
• Google Cloud Platform: Cloud Run, GKE, Datastore, Pub/Sub.

This role sits at the intersection of AI engineering and application development. You’ll build customer-facing features from scratch, while also helping us integrate and scale the AI infrastructure that power them. You're deeply fluent in TypeScript and React, strong enough on the backend to own a feature end-to-end, and have meaningful experience building AI applications. You craft fast, polished, reliable software and you're drawn to problems that are genuinely unsolved.

We're looking for full stack engineers and those who lean more towards frontend.

Full stack. You understand applied AI well past the API layer: building systems that stay reliable when the model is unpredictable, writing evals that surface real signal, designing agentic workflows that hold up under production conditions. You've shipped RAG, tool calling, memory, or multi-agent patterns to real users and you know where each one breaks down.

Frontend. You notice things other engineers don't. The easing curve that's slightly off. The transition that happens too fast to register. The empty state that was clearly an afterthought. In a product where AI does most of the heavy lifting, the interface is where trust is built or broken — and you hold that line. You've built design systems from the ground up and have a point of view on motion, interaction, and what makes an AI-generated surface feel considered rather than random.

What we look for

• Production-grade React, NextJS, and TypeScript
• Strong backend experience: async systems, API design, schema decisions, scaling under real load
• For full stack: applied AI in production like RAG, tool calling, memory, multi-agent patterns, and the ability to write evals and reason about whether a system is actually improving
• For frontend: design systems, animation and motion, data-fetching patterns (TanStack Query, tRPC), and deep care for browser fundamentals and performance
• Familiarity with our infrastructure and AI tooling (Cloudflare Workers/Durable Objects, Postgres + PGVector, LangSmith, Inngest) is a plus

What success looks like

Features that are fast, reliable, and polished. Architectural and interaction decisions that make the next thing faster to build. You raise the bar for the people working alongside you.

Application process

Your works speaks louder than your resume. We want to see how you think, what you've made, and how you work with AI. Our application asks for three things:

1. A Loom video (2-3 minutes)

Tell us who you are, what you're working on or have recently built, and how AI is a core part of how you work. Don't script it. We want to see how you think out loud.

2. Something you've built or designed 

A link, a side project, a campaign. Anything that shows what you're capable of making. One strong example beats ten weak ones.

3. A few short questions

1. Why Durable 
2. Where are you located
3. What are your salary expectations

Fine print

We are a Vancouver-based company and candidates need to be based in Canada. Remote is fine - you can expect travel to Vancouver once per quarter (minimum) to work in-office with the team. 

Compensation is $180,000–$225,000 CAD base plus equity, for Vancouver-based candidates. Actual salary takes experience, location, and other factors into account.

Tech stack 

Languages: Typescript, SQL, Bash, HTML5, CSS3, Python

Frameworks/Libraries: React, NextJS, React Query, React Native, Expo, TailwindCSS, RadixUI, DrizzleORM, trpc, NodeJS, Bun, WebRTC, PyTorch

Tooling: Turborepo, ESLint, Prettier, NPM/PNPM, Git, AI codegen

Databases: Postgres (including PGVector and JSON datatype), Object stores

Infrastructure: Docker, Cloudflare (Workers, Durable Objects, Pages, DNS, CDN), Vercel, Inngest, Render, Trigger.dev, Datadog, Together.ai, LangSmith, Hugging Face, Replicate, Langfuse

AI engineering: Large Language Models, Multi-Modal Models, Image Generation, In-painting, Voice Models

AI concepts (learn over time): Basic Prompting, Chain of Thought prompting, N-shot prompting, Prompting reasoning models, Tool calling, Preprocessing unstructured data, ReAct, Agent basics, Advanced agentic patterns, Evals, Memory, Generative UI, Streaming, Real-time, Multi-agent systems, Guardrails, Citations, Vector databases, RAG, Text embeddings, Knowledge graphs, Query routing, Synthetic data, Fine-tuning, RLHF, Diffusion Models, MCP, Computer use, Using/Serving Multi-modal OSS models