Senior AI Engineer

About Traffic Label

Traffic Label is a fast-growing, data-driven technology company operating in the iGaming and affiliate marketing space, building scalable products focused on performance, analytics, automation, and intelligent systems across multiple brands and global markets.

Role Overview

We are looking for a Senior AI Engineer to design and build AI-powered systems that automate business workflows, enhance decision-making, and deliver intelligent products across our platform.

This is not a research role. You will build production systems that use LLMs, retrieval, and agentic patterns to solve real problems - automating multi-step processes, enriching data pipelines, and putting humans on the loop (supervising) rather than in the loop (doing).

You will work across our affiliate marketing, data, and content platforms - designing workflows that range from deterministic (rule-based) to probabilistic (model-driven) automation.

Team Context

You'll be part of a new AI function being built within the engineering organisation. You'll initially report to the CTO while the team scales, working alongside backend engineers, data engineers, and product owners. This is early-stage AI work — you'll help define the roadmap alongside product and business stakeholders, shape the architecture, and choose the tooling. If you thrive in ambiguity and want to build something from zero, this is for you.

Key Responsibilities

• Design and build automated workflows - both deterministic (rule-based) and probabilistic (model-driven)

• Implement agent orchestration patterns (planning, tool use, evaluation loops, error recovery)

• Build and maintain APIs and backend services supporting AI-driven functionality

• Develop retrieval and grounding systems for knowledge search and context enrichment

• Work with structured and unstructured data to support AI use cases

• Design evaluation frameworks to measure and monitor AI system quality

• Design testing strategies for non-deterministic AI systems

• Manage cost, latency, and quality tradeoffs in production AI systems

• Collaborate with Backend, Data, DevOps, and Product teams

• Deploy, monitor, and maintain services in production environments

• Contribute to system design and technical decision-making

Skills & Experience

Required:

• Senior-level engineering experience (typically 4+ years) in backend or software engineering (Python strongly preferred)

• Practical experience building AI-powered applications in production (not just prototypes)

• Experience with LLM APIs, context engineering, and AI integration patterns

• Understanding of agentic patterns: multi-step orchestration, tool-calling, state management

• Experience with retrieval and grounding systems (RAG, semantic search, knowledge retrieval)

• Solid software engineering fundamentals (API design, system design, databases)

• Experience with data processing and working with structured/unstructured data

• Familiarity with cloud platforms (AWS preferred)

• Experience with Docker and CI/CD workflows

• Strong debugging and problem-solving skills

• Ability to take ownership and work independently

Preferred:

• Experience with agent orchestration frameworks (open-source or custom)

• Experience designing human-on-the-loop oversight and approval workflows

• Familiarity with AI evaluation and observability (output quality measurement, drift detection, cost monitoring)

• Exposure to the affiliate marketing or iGaming industry

• Experience working in a fast-paced technology startup environment

What We Offer

• Full remote work flexibility

• Competitive compensation discussed at first conversation

• Generous paid time off including vacation, sick leave, and public holidays

• Budget for learning, experimentation, and conference attendance

• Opportunity to build AI systems from the ground up in a high-growth business

• Small, senior engineering team — high autonomy, low bureaucracy

• Strong ownership culture and direct influence on technical direction

• Career growth across AI engineering, platform architecture, and technical leadership