AI ENGINEER

About Atos Group

Atos Group is a global leader in digital transformation with c. 67,000 employees and annual revenue of c. 10 billion, operating in 61 countries under two brands - Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Position: AI Engineer - Applied AI

Location: San Diego, CA (full time on-site)

Overview

The client is looking for a strong leader to shape their AI roadmap and drive applied AI engineering work. The focus is on accelerators across product, engineering, and QA. We are looking for someone who is both strategic and hands-on. Must be able to: - Set direction for AI for a key Atos client. - Work closely with senior stakeholders. - Confidently demonstrate capability in live technical discussions (for example, AWS configuration and coding exercises). Key responsibilities - Shape and own the AI roadmap for a key client, aligning closely with business and technology leaders. - Lead the definition and delivery of applied AI accelerators across product, engineering, and QA. - Provide strategic guidance on how AI can be used to improve products, engineering practices, and quality assurance. - Stay tuned into current AI trends and help the client "surf the AI tides" in a practical, value-focused way. - Collaborate with Atos and client teams to ensure AI initiatives are realistic, testable, and deliverable. Mandatory requirements - Strong background in AWS-based engineering or architecture, with the ability to discuss and demonstrate AWS configuration in practical scenarios. - Solid experience in software engineering or AI engineering, including the ability to participate in live coding or technical problem-solving. - Ability to evaluate and select appropriate AWS AI/ML services as part of an overall AI roadmap and reference architecture. - Proven ability to lead or significantly influence technology direction in a senior role - Build business cases that connect AI investments to measurable outcomes (cost reduction, velocity improvement, quality metrics) - Excellent communication skills and the ability to work effectively with product, engineering, QA, and business stakeholders. - Local or nearby to San Diego, with the ability to be in the office at least twice per week. Preferred requirements - Experience in an AI Engineering or AI Architect role, particularly with applied AI accelerators for product, engineering, and QA. - Experience working on AI-related initiatives that touch product development, engineering practices, and QA. - Experience with key AWS AI services such as Amazon Bedrock and Amazon SageMaker, and how they fit into end-to-end AI solutions. - Actively "surfing the AI tides": aware of current AI developments, passionate about applied AI, and always curious. - A clear "walk the talk" track record: hands-on, comfortable with practical assessments such as live coding and AWS configuration, and flexible in attitude and ways of working. Advanced AI Capabilities - Experience with Generative AI and LLMs: fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), vector databases - Hands-on experience with modern AI frameworks and tools: - LLM Frameworks: LangChain, LlamaIndex, HuggingFace - Vector Databases - Model Serving - Previous work on AI accelerators specifically for product development, engineering productivity, or QA automation Technical Foundation Required Skills & Experience - 7+ years in software engineering with 3+ years focused on AI/ML engineering or architecture - Deep expertise in Python with production experience in ML frameworks (PyTorch, TensorFlow, scikit-learn) - Strong knowledge of AWS cloud architecture with ability to design and implement - Strong experience with RAG systems and vector databases - Deep understanding of AWS services and architecture - Experience with large language models and prompt engineering - Deep understanding of Agentic AI and MCP. - Background in data processing and ETL pipeline development

Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.

Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment.

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