Thiga

Marketing Operations

• En tant que Marketing Operations Specialist, tu es le moteur qui transforme notre stratégie marketing en réalité opérationnelle.
• Tu pilotes la logistique de nos webinars, meet-ups et de notre événement phare, La Product Conf Paris.
• Tu es l'interface privilégiée de nos prestataires (agences, freelances, imprimeurs) pour garantir des livrables de haute qualité.
• Tu supervises la production multimédia (vidéos, podcasts, shootings) et assures la diffusion sur nos canaux.
• Tu gères les workflows, les landing pages et l'optimisation des assets pour convertir nos prospects en MQLs puis SQLs.
• Tu lances des campagnes multicanales (Online/Offline) et analyses les KPIs pour ajuster le tir.
• Tu gardes un œil affûté sur le marché et la concurrence pour proposer des messages et idées toujours plus impactantes.

Apprenti(e) – Marketing Operations Specialist

Scrum Master

• Vous intervenez au cœur d’une équipe Produit avec un objectif clair : rendre le Delivery plus fluide, plus prévisible et plus robuste.
• Vous ne vous contentez pas d’animer les rituels. Vous analysez, challengez, structurez et agissez.

Scrum Master / Coach

AI Engineer

• Architect Agent Systems: Design agents using tools such as LangGraph or AutoGen.
• Inference Optimization: Experiment with latency/cost/quality trade-offs (quantization, semantic caching, selecting SLM vs LLM models).
• RAG: Implement Retrieval-Augmented Generation approaches.
• Fine-tuning & Local LLMs: Explore self-hosting (vLLM, Ollama) and fine-tuning models on specific datasets.
• Industrialization (LLMOps): Set up robust evaluation pipelines (LLM-as-a-judge, Ragas, DeepEval) to ensure non-regression and factuality.
• Full-stack AI integration: Connect the "brains" (LLMs) to data (APIs, SQL/NoSQL databases, vector stores) via an agent-based approach.
• Architecture audit: Analyze clients' agentic architecture implementations for optimization or redesign.

Solutions Engineer

• Architect Cloud & GenAI platforms: design reference architectures (multi-tenant, event-driven, API-first) to deliver products in a robust and secure way
• Cost / Latency / Reliability optimization: define performance and FinOps strategies (caching, autoscaling, serverless vs containers, CPU/GPU scheduling, multi-model approaches for AI) and measure their impact on SLOs
• Data & retrieval on cloud: design the data foundation for cloud and GenAI workloads
• Build vs buy approaches: evaluate and integrate managed vs self-hosted solutions, using a pragmatic decision framework
• Industrialization (DevOps / SRE / Platform Engineering): establish a delivery platform (CI/CD, GitOps, IaC) and reproducible environments for traditional cloud applications and AI workloads
• Security & compliance by design: implement IAM, secrets management, encryption, network policies, auditing, data boundaries, and optionally for AI red teaming and GenAI guardrails (content filtering, prompt-injection mitigation, output constraints)
• Architecture audits: analyze client platform scalability (quotas, rate limiting, contention, costs, availability, DR/BCP) and propose modernization roadmaps

Apprenti(e) – Marketing Operations Specialist

Scrum Master / Coach

AI Engineer

Solutions Architect, Cloud & GenAI