Senior AI Engineer (Generative AI & Agents)

About Prosus AI Team
At Prosus, we integrate generative AI across our global portfolio—from education and food delivery to classifieds and online payments. Based in Amsterdam and collaborating with teams in 40+ countries, we use foundational models to build generative AI solutions and autonomous agents that set new standards in user interaction and operational efficiency.
About the roleAs an AI Engineer, you will design, build, and operate production AI services and agentic workflows. You’ll partner with data scientists and product/engineering teams to take ideas from prototype to reliable, secure, cost‑efficient deployment—owning context/memory, tooling, evaluations, and inference performance end‑to‑end.

Key Responsibilities

• Design and implement LLM‑powered services and agentic workflows (context engineering, memory, tool use/orchestration) for real customer and operations use cases.
• Build and maintain evaluation pipelines (datasets, leaderboards, automated + human evals) to ensure quality, safety, and regression control.
•  Productionize models and model APIs on cloud infrastructure (containerization, CI/CD, feature flags, canary releases, observability, incident response).
• Optimize inference for latency, throughput, and cost (batching, caching, prompt/program optimization; use of suitable inference servers).
• Implement retrieval and memory systems (vector search, session/long‑term memory) that improve agent reliability over time.
• Create data flywheels: instrument applications, collect feedback, curate datasets, run targeted fine‑tunes/adaptations, and close the loop with evals.
• Harden systems for security, privacy, and compliance (PII handling, guardrails, content filtering, auditability, documentation).
• Improve developer ergonomics (internal tooling, SDKs, prompt libraries, testing harnesses) to speed up safe experimentation.
• Collaborate cross‑functionally with product, design, and operations; participate in backlog refinement and share learnings across the stack.

Minimum Qualifications

• Bachelor’s or Master’s in Computer Science/Engineering or equivalent practical experience.
• 6+ years in software/ML engineering delivering production systems with at least +2 years of  experience working in complex tech infrastructure.
• Strong Python and OOP; you write clean, testable, maintainable code.
• Experience building backend services/APIs, containers (e.g., Docker), and CI/CD.
• Hands‑on integrating hosted and/or open‑source LLMs via SDKs or APIs into applications.
• Practical understanding of ML fundamentals (model lifecycle, metrics, failure modes) and experience adapting models or prompts to meet product goals.
• Experience with cloud infrastructure on at least one major provider (AWS/Azure/GCP). AWS experience is a plus but not required.
• Familiarity with retrieval/vector search and evaluation design (offline tests, task design, human‑in‑the‑loop).
• Comfort measuring reliability and performance using any modern observability stack (metrics, logging, tracing).

Preferred Qualifications

• Experience with a deep learning framework (e.g., PyTorch, TensorFlow, JAX) and model libraries (e.g., Hugging Face or similar).
• Knowledge of LLM inference servers and optimization techniques (e.g., vLLM/TGI/TensorRT‑LLM—or equivalent).
• Exposure to distributed systems and performance engineering (profiling, async, parallelism).
• Data engineering exposure (orchestrators, batch/stream processing) and testing for prompts/LLM programs.
• Familiarity with security/privacy best practices for AI systems.
• Experience working across multinational teams.

Personal Attributes

• Strong analytical and organizational skills; ownership mindset and bias to action.
• Excellent communicator—clear on trade‑offs with technical and non‑technical audiences.
• Collaborative team player who can also lead project segments independently.
• Curious, pragmatic, and adaptable—comfortable switching between research, engineering, and data work.
• Proactive about documentation, reproducibility, and continuous improvement.

What You’Ll Work On (Examples)

• Advance context engineering, memory, tooling, and evaluations to ship reliable “agentic” features.
• Optimize our Agentic Workforce application end‑to‑end for quality and performance.
• Improve internal tools and developer ergonomics to accelerate experimentation and delivery.
• Be the team’s prompt/programming expert and raise the quality bar across products.

What We Offer

• The chance to build production generative AI at global scale across diverse businesses.
• A collaborative, supportive environment where innovation and initiative are encouraged.
• Modern tooling, mentorship, and clear growth paths across the Prosus portfolio.
• A diverse, inclusive workplace where all voices are heard and valued.

Our Diversity & Inclusion Commitment
We respect the dignity and human rights of individuals and communities wherever we operate in the world. Building an inclusive workplace where everyone feels welcome and can thrive is critical for us. We provide access to education, which helps everyone understand the important role they play and the positive impact they can have.
For a deeper look at our journey and future plans, explore our latest Annual Report. Stay up to date with our latest news to see what makes Prosus stand out. Learn more at www.prosus.com.