Job Description

🧠Senior Backend Engineer (LLM / AI Experience)

Hybrid · Tech Team · Full-time
📍 Barcelona, Spain

In a few words

• Build and scale backend systems powering conversational AI & digital humans
• Hands-on senior role balancing architecture + production code
• Work deeply with LLMs, RAG pipelines, and real-time systems

• 📍 Barcelona (hybrid) or remote in Europe | 💰 €50k–€65k

Why this role is exciting: You’ll shape the backend foundations of a cutting-edge digital human platform, where your architectural and performance decisions directly impact real-time AI experiences used by enterprise customers.

About UNITH

At UNITH, we’re transforming customer journeys with conversational AI. Listed on the ASX, we create lifelike digital humans using cutting-edge synthetic facial movement, voice engineering, and conversational design.

Our digital humans speak 60+ languages with 600+ voices, redefining how businesses interact with customers worldwide.

🚀 The Role

We’re looking for a Senior Backend Engineer with recent LLM product experience who combines strong architectural thinking with hands-on development.

You’ll work closely with the Head of Engineering, playing a key role in technical decisions while remaining deeply involved in day-to-day coding, feature delivery, and system optimization. You’ll be a senior technical voice on the team — someone who designs systems and builds them.

🛠️ What You’ll Do

Architecture & System Operations (50%)

• Actively participate in architectural decisions with the Head of Engineering
• Collaborate with the Cloud Infrastructure Engineer on platform architecture, observability (monitoring, logging, alerting), and deployment strategies
• Design and optimize systems: performance profiling, database queries, caching, and resource usage
• Own production operations: troubleshooting, incident response, and on-call
• Provide technical guidance through code reviews, design discussions, and best practices
• Collaborate on real-time streaming architecture with the Video Synthesis Engineer

Feature Development & Implementation (50%)

• Implement backend features and services in production-grade Python and Go
• Build conversation features: state management, history, and intelligence improvements
• Implement multi-document knowledge bases using AWS Bedrock
• Integrate LLM APIs (OpenAI, AWS Bedrock) and build RAG pipelines
• Develop APIs and service integrations (gRPC, REST)
• Work on core backend services: orchestration, caching, and platform APIs
• Own testing, CI/CD pipelines, and deployment automation

🧰 Tech Stack

• Python (FastAPI) and Go (gRPC services)
• AWS (S3, EC2, Lambda, Bedrock, managed services)
• Docker, Kubernetes, RabbitMQ, Redis
• LLM APIs (OpenAI, AWS Bedrock)

✅ What We’re Looking For

Must-Have

• 5+ years of backend engineering experience with distributed systems, microservices, and real-time architectures (WebSocket, gRPC, event-driven)
• Experience building and deploying complex, highly-performant Python applications
• 2+ years building LLM-powered products in production (2022–2025), including hands-on experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock) and RAG systems
• Comfortable balancing architecture design with hands-on implementation
• Strong AWS experience with focus on performance optimization, observability, and production operations
• Proven ability to optimize production systems (latency, throughput, technical debt)
• Excellent collaboration skills across backend, infrastructure, and AI/ML teams

Bonus Points

• Golang experience
• Experience with video streaming, media processing, or conversational AI platforms
• Data engineering or ML model serving infrastructure experience

🎯 What Success Looks Like

First 6 months

• Knowledge transfer completed and ownership of critical backend services established
• Multi-document knowledge base and conversation features live in production
• Active contributor to architecture discussions with measurable performance improvements
• Production systems well-monitored with improved observability

First 12 months

• Core backend services and RAG pipeline running reliably in production
• Platform-wide performance optimizations delivered (Q1–Q3 targets met)
• Backend engineers unblocked and supported through your technical guidance
• Recognized as the go-to expert for backend + LLM implementation

💼 What We Offer

Compensation & Flexibility

• 💰 Salary: €50,000 – €65,000, depending on experience
• 🏠Hybrid work in Barcelona or remote options within Europe

Impact & Growth

• Ownership of critical backend services used daily by enterprise customers
• Hands-on technical work alongside architectural responsibility
• Deep technical challenges across LLMs, RAG pipelines, real-time systems, and scalability
• High-impact role in a small, senior team (12 people)
• Close collaboration with Engineering, AI research, and infrastructure teams
• Opportunity to build expertise in the fast-evolving digital humans domain

Additional Perks

🏙️ Office in the center of Barcelona

🌍 Work from anywhere

🍽️ Lunch compensation when in the office

🩺 Private health insurance with Alan

🚍 Travel allowance (for team members living 10km+ from the office)

🧾 Flexible benefits (tax-free under Spanish legislation)

🏋️ ClassPass discount

📩 How to Apply:

Submit:

· Your CV highlighting ML production experience

· A short motivation (3–5 sentences) covering:

• Backend systems you’ve built and maintained
• LLM features you’ve implemented in production
• A performance optimization project you worked on
• Your experience with RAG or knowledge bases
• Why digital humans excite you

Apply via the Easy Apply button, or reach out directly to joyce@unith.ai — creativity is welcome 🤖

🔍 Recruitment Process

1. Intro call with Joyce (30 min)

2. Technical interview with Head of Engineering & Product Manager (90 min)

3. Team meeting with backend video synthesis, and/or infrastructure engineers (90 min)

4. Practical exercise (short, relevant implementation task)

5. Reference check

⏱️ Timeline: 2–3 weeks from application to offer

Ready to make digital humans faster, better, and more reliable?
👉 Apply now