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Traffic Label

Traffic Label

Senior AI Engineer

Role

Senior AI Engineer

Job type

-

Found on Mokaru

3 days ago

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Salary

Not disclosed by employer

Job description

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

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