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\uD83D\uDC6B About the team At Equativ, we’re on a mission to develop advertising technologies that empower our custo...

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Selected role

AI Engineer [Feelance]

EQUATIV Paris, A8, FR

Senior Full-time

\uD83D\uDC6B About the team

At Equativ, we’re on a mission to develop advertising technologies that empower our customers to reach their digital business goals. This means that we rely on massively scalable, widely distributed, highly available, and efficient software systems; the platform deals with over 3 million requests per second (+250 billion/day) managed by 3,000 servers with less than 250ms response time.

Our innovation team based in Paris, Nantes, Bordeaux, Limoges, Krakow and Berlin is composed of 150+ straightforward and energetic engineers working in an Agile environment and ready to tackle the most complex technical challenges.

About the team

At Equativ, we're on a mission to develop advertising technologies that empower our customers to reach their digital business goals. The impact of Generative AI is projected to disrupt part of the industry, and Equativ has been undergoing a significant transformation to embed this technology at the core of its value proposition.

The GenAI team is a new, strategic unit (6–8 people) responsible for the design, development, and deployment of Equativ's entire GenAI stack. Our work is split across two complementary pillars:

Core Platform — designing and building a reusable, industrialized Agentic Platform (MaaS, AaaS — Model/Agent as a Service) to accelerate agent development across the company.
Business Feature — developing and deploying mission-critical AI agents that automate workflows for internal teams (operations, ad quality, marketplace, etc.).

You can join either pillar depending on profile fit, and we routinely rotate engineers between the two as priorities and product opportunities evolve. This means the bar on technical depth is consistent across both teams: we hire the engineer first, allocate the team second.

Both teams sit inside the R&D department (200+ engineers across Paris, Nantes, Limoges, Krakow, Berlin and North America), all working in an Agile environment.

What you will do

Depending on the pillar you join, expect a mix of the following:

Build production agents — design, develop, and deploy goal-oriented AI agents and multimodal/conversational experiences using frameworks like Google ADK, Langchain, LangGraph, combined with orchestration tools like n8n where appropriate.
Own the production lifecycle of what you ship — establish robust AIOps/AgentOps practices (monitoring, versioning of agent blueprints, evaluation pipelines, reliability) within your team's scope.
Contribute to the shared Agentic Platform (Core pillar) — gateways, evaluation frameworks, observability, MaaS/AaaS APIs — so feature teams build faster on solid foundations.
Build agent-side integrations (Feature pillar) — develop the MCP servers and backend services that agents need to interact with enterprise systems, in partnership with other R&D teams (and picking up the work yourself when a partner team doesn't have bandwidth).
Be the Python referent in your team — own production-quality Python, enforce strong SWE principles (unit tests, CI/CD, Git, code review), and bring AIOps/MLOps best practices wherever you sit.
Build a working expertise on agentic design patterns (eval, guardrails, multi-agent orchestration) and share it with AI champions and AI builders across the company as the GenAI Center of Expertise takes shape.
Engage with stakeholders — talk to internal teams to understand operational pain points and translate them into measurable GenAI solutions. You don't lead cross-team architecture, but you should be credible across the org.

About you

Master's degree in Computer Science, Data Science, or a similar technical field.
3+ years as a Python Developer or ML Engineer, with a recent focus on deploying LLM-powered solutions in production.
Mastery of Python for enterprise-level development, strong knowledge of core software engineering principles, and hands-on experience with AIOps/MLOps (unit tests, CI/CD, Git, observability). You should be comfortable being your team's reference on these topics.
Proven experience building production-ready agent workflows, orchestration layers, or platforms using Python frameworks (ADK, Langchain, LangGraph).
Practical experience with modern cloud platforms (Vertex AI, Kubernetes or equivalents) for deploying scalable GenAI services.
Strong versatility and a demonstrated willingness to work across the full stack and across functional expertises.
Entrepreneurial mindset, high autonomy, and the ability to turn ambiguous, high-level business goals into concrete, efficient GenAI features.
Fluent technical English (written and verbal) — mandatory.

\uD83D\uDC4B **About us

Equativ**, a leading independent ad platform, brings scale and simplicity to digital advertising.

Following its recent merger with Sharethrough and the acquisition of Kamino Retail, advertisers, media owners, and technology partners rely on Equativ’s advanced SSP, curation, and retail media services and technology to achieve maximum business outcomes.

With a focus on privacy-first programmatic video, CTV, and data-driven solutions, Equativ enables clients to activate across the digital ecosystem while protecting consumer privacy.

The company’s global expertise is also backed by a team of over 750 employees across 19 countries.

As a proud recipient of the HappyIndex@Work label, Equativ is committed to providing a dynamic, flexible workplace where employees thrive, grow, and excel in both their professional and personal lives.

Come and lead the charge with us in building a transparent ecosystem based on quality!

Equativ is an equal opportunity employer. Equal access to employment, services, and programs are available to everyone, regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If you require reasonable accommodation throughout the application and/or interview process, please contact the recruitment team at [email protected]

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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