AI Engineer – Agent Specialist

Ambience Services

. Design, build, and optimize AI-driven agents and autonomous workflows .

Posted 11/4/2026full-timeTavros • GreeceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing AI-driven agents and workflows, with strong capabilities in machine learning model development and deployment. Proficient in cloud services and modern delivery practices, ensuring scalable and reliable AI solutions tailored to business needs.

Highest-signal resume keywords

AI Agent DevelopmentMachine Learning Model DeploymentCloud Services (AWS, Azure, GCP)Python EngineeringAgile Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData Pipeline ArchitectureModel-Serving InfrastructureAI Techniques PrototypingAPI DevelopmentTesting and Code ReviewsLLM Application PatternsDockerCI/CD PracticesMonitoring and Scaling

Soft Skills

Strong Communication SkillsProactive ApproachOwnership Mindset

Tools & Technologies

AWS (S3, IAM, CloudWatch, SageMaker, ECS/EKS)AzureGCPMonitoring ToolsContainer Platforms

Industry Keywords

B2B EnvironmentsStartupsHigh-Growth EnvironmentsAutomation Opportunities

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Design, build, and optimize AI-driven agents and autonomous workflows
Develop, fine-tune, and evaluate machine learning models for production use
Architect and implement data pipelines, model-serving infrastructure, and agent orchestration components
Lead experimentation, research, and prototyping of new AI techniques and agent frameworks
Advise internal teams, and later external clients, on automation opportunities, and design and deliver AI agents tailored to their workflows
Collaborate with cross-functional teams to integrate AI capabilities into applications and platforms
Ensure performance, reliability, and scalability of deployed models and agent systems
Contribute to technical strategy and mentor other engineers in AI best practices

Requirements

What you’ll need

BSc/MSc in Computer Science, Engineering, or a related field (or equivalent practical experience)
Proven track record of building and deploying at least 3 AI agents in production environments, delivering measurable outcomes for real-world business use cases
Strong Python engineering skills (APIs, testing, code reviews, clean design)
Practical experience with LLM application patterns (agents/tool-use, prompting, and/or RAG)
Hands-on cloud experience building and operating services on AWS, Azure, or GCP (e.g., storage, identity and access management, monitoring, and either a managed ML platform or a container platform)
Comfortable with modern delivery practices (Docker, CI/CD) and production operations (monitoring, scaling, cost awareness)
Ownership mindset and a proactive, self-driven approach: you identify opportunities on your own, translate business needs into technical solutions, and deliver iteratively
Strong communication skills, with the ability to explain AI concepts to non-technical stakeholders and guide internal teams and clients through adoption
Experience with AWS (e.g., S3, IAM, CloudWatch, SageMaker, ECS/EKS)
Background in startups or high-growth environments
Experience in B2B environments
Experience with Agile methodologies

Benefits

Comp & perks

Competitive renumeration package
Private medical insurance
Performance based bonus
Training & development opportunities
A team that loves innovation, quality, and having fun at work
Work-life balance