AWS AI Engineer

We are seeking a Senior AWS AI Engineer to join our growing AI engineering team. You will be a key player in designing building and deploying production-grade AI agents and generative AI solutions on AWS. This role requires hands-on expertise across the AWS AI stack (Amazon Bedrock Bedrock AgentCore Amazon SageMaker and Amazon Q) combined with the engineering rigor to take agentic systems from proof-of-concept to reliable secure and scalable production. You will be a trusted advisor to our customers driving the adoption of agentic and generative AI and shaping the next generation of intelligent solutions Devoteam delivers.

Responsibilities:

• Customer obsession: Act as the go-to AI engineering expert for our key customers translating business challenges into production-ready agentic AI solutions and supporting pre-sales solutioning and proof-of-value engagements.
• AI Agent Development: Design build and ship autonomous and multi-agent systems in production using Amazon Bedrock and Bedrock AgentCore together with frameworks such as Strands Agents LangGraph or CrewAI covering tool use orchestration memory identity and human-in-the-loop patterns.
• Generative AI & Model Engineering: Select evaluate and integrate foundation models on Amazon Bedrock; design implement and evaluate RAG pipelines (including retrieval quality and RAG evaluation); apply prompt engineering and model customization; and leverage Amazon SageMaker for building and deploying classical (non-generative) machine learning models and for the broader ML lifecycle - training hosting and monitoring - where appropriate.
• Architecture & Design: Design highly available scalable and secure AI architectures on AWS applying the Well-Architected Framework and generative-AI best practices. Contribute to the overall AI strategy reference architectures and reusable accelerators.
• Production Engineering & LLMOps: Operationalize AI agents end-to-end automated AI agent evaluation guardrails observability cost and latency optimization CI/CD and Infrastructure as Code (Terraform CloudFormation AWS CDK). Own the reliability quality and performance of deployed agents.
• Responsible AI & Security: Implement responsible-AI guardrails data privacy and security controls (Amazon Bedrock Guardrails IAM encryption PII handling) and ensure compliance with relevant frameworks (e.g. ISO 27001 GDPR EU AI Act).
• Autonomy & Ownership: Work autonomously across the full delivery lifecycle from discovery and design to deployment and handover making sound technical decisions with limited supervision while keeping stakeholders aligned. Participate in support or on-call rotations where the customer assignment requires it.
• Collaboration & Communication: Collaborate with data platform and software engineering teams and communicate clearly with both technical and non-technical stakeholders. Mentor junior engineers and share knowledge across the practice.

Continuous Improvement: Stay current with the fast-moving AWS AI landscape (Bedrock AgentCore SageMaker Amazon Q and emerging capabilities) and proactively bring new patterns tooling and ideas into our delivery

Qualifications :

• Bachelors or Masters degree in Computer Science AI/Data Science Engineering or a related field or equivalent practical experience.
• 4 years of experience working with cloud platforms including hands-on experience building and deploying solutions on AWS.
• Proven experience designing building and running AI agents or generative AI applications in production not only prototypes or notebooks.
• Hands-on experience with the AWS AI/ML service stack including Amazon Bedrock Bedrock AgentCore Amazon SageMaker and Amazon Q.
• Solid understanding of generative AI and agentic concepts: foundation models prompt engineering RAG and RAG evaluation vector databases tool/function calling multi-agent orchestration memory and AI agent evaluation.
• Practical experience with at least one agent framework (e.g. Strands Agents LangGraph LangChain CrewAI or the Bedrock Agents SDK).
• Experience developing traditional (classical) machine learning models such as classification regression forecasting or clustering and managing their lifecycle on Amazon SageMaker (data preparation training deployment and monitoring).
• Strong proficiency in Python together with solid software engineering practices (version control testing code review).
• Experience with Infrastructure as Code (Terraform CloudFormation or AWS CDK) and CI/CD pipelines for deploying AI/ML workloads.
• Good understanding of AWS core services (IAM S3 Lambda VPC API Gateway ECS/EKS) and security best practices.
• Demonstrated ability to work autonomously and own delivery end-to-end in a customer-facing or consulting context.
• Excellent problem-solving skills and the ability to make pragmatic trade-offs in ambiguous fast-moving environments.
• Strong communication and stakeholder-management skills.
• AWS Certifications (e.g. AWS Certified Generative AI Developer Professional AWS Certified Machine Learning Specialty AI Practitioner or Solutions Architect) are a strong plus.
• Fluent English and Dutch (French is a plus)

 Bonus if you have experience across one or more of the following areas:

• Experience with LLMOps / MLOps tooling (model evaluation observability prompt management guardrails A/B testing).
• Experience fine-tuning or customizing foundation models and with knowledge bases and vector stores (e.g. Amazon OpenSearch Aurora pgvector Amazon Kendra).
• Experience deploying Amazon Q Developer or Amazon Q Business in enterprise settings.
• Experience with other public cloud AI platforms (e.g. Azure OpenAI Service Google Vertex AI).
• Contributions to open-source AI projects publications or a public portfolio of agentic AI work.

Additional Information :

Why choose us

• Impact: A key role in a fast-growing ambitious international tech consultancy.
• Culture: A collaborative dynamic and genuinely tech-savvy team environment.
• Growth: Continuous learning opportunities and a clear career path.
• Package: A competitive salary package with a company car (or mobility budget) and premium benefits.
• Work-Life Balance: We believe in a healthy work-life balance ensuring that you have time to unwind pursue your hobbies and spend quality time with loved ones

At Devoteam we combine strong values respect frankness ambition entrepreneurship & collaboration with a fun environment that empowers you to innovate and succeed.

Remote Work :

No

Employment Type :

Full-time