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
- Bachelor’s or Master’s 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.
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.