AI Software Engineer

HarborLab

AI Engineer designing and building AI-powered systems for a maritime tech company. Focus on practical AI workflows, backend services, and cross-functional collaboration.

Posted 7/7/2026full-timeAthens • 🇬🇷 GreeceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI Systems and LLM Engineering, with strong capabilities in Backend Development using Python and frameworks like FastAPI. Proficient in deploying and optimizing AI systems in production environments while collaborating effectively across cross-functional teams.

Highest-signal resume keywords

AI & LLM ExpertiseBackend Engineering SkillsProduction AI & MLOpsTechnical Stack ExperienceCloud & DevOps

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAPI DesignMachine LearningAI EngineeringPrompt EngineeringModel EvaluationAsynchronous ProcessingClean ArchitectureTestingDebugging

Soft Skills

Strong Communication SkillsCollaboration

Tools & Technologies

FastAPIPyTorchScikit-learnPandasPydanticHugging FaceLangChainFAISSPineconeDocker

Industry Keywords

MaritimeShippingLogisticsSupply-ChainAI Workflow OrchestrationModel Provider IntegrationEvaluation FrameworksLLM ObservabilitySecurityCompliance

Tech Stack

Tools & technologies

AWSCloudDockerElasticSearchKubernetesPandasPythonPyTorchScikit-Learn

About the role

Key responsibilities & impact

AI Systems & LLM Engineering: Design and build modern AI applications using LLMs, RAG, agents, embeddings, vector databases, and advanced prompting techniques. Develop AI workflows that are reliable, measurable, and production-ready.
Backend Development: Build scalable backend services and APIs in Python, using frameworks such as FastAPI. Integrate AI models into existing systems with clean architecture, strong typing, validation, testing, and maintainable code.
Data & Retrieval Infrastructure: Work with structured and unstructured data, document pipelines, embeddings, semantic search, and retrieval systems using tools such as FAISS, Pinecone, Weaviate, or similar technologies.
Production AI & MLOps: Deploy, monitor, and improve AI systems in production. Work on evaluation pipelines, observability, latency optimization, cost control, error handling, model versioning, and CI/CD workflows.
Cross-Functional Collaboration: Collaborate with software engineers, data scientists, product managers, and maritime experts to define requirements, validate solutions, and deliver business impact quickly.
Documentation & Knowledge Sharing: Maintain clear technical documentation for architecture, APIs, prompts, evaluation methods, deployment processes, and operational decisions.

Requirements

What you’ll need

Educational Background: BSc or MSc in Computer Science, Engineering, Mathematics, Physics, or another STEM field.
Professional Experience: 3+ years of experience in machine learning, AI engineering, backend engineering, or a related technical role.
Backend Engineering Skills: Strong Python experience and solid software engineering fundamentals, including API design, testing, debugging, clean architecture, asynchronous processing, and production-grade code.
AI & LLM Expertise: Hands-on experience with LLMs, RAG systems, embeddings, prompt engineering, model evaluation, and AI workflow orchestration.
Technical Stack: Experience with tools and libraries such as PyTorch, Scikit-learn, Pandas, Pydantic, FastAPI, Hugging Face, LangChain, LlamaIndex, or similar frameworks.
Vector Search & Retrieval: Experience with vector databases or similarity search tools such as FAISS, Pinecone, Weaviate, Qdrant, or Elasticsearch/OpenSearch.
Model Provider Integration: Familiarity with AI models and APIs from providers such as OpenAI, Anthropic, Google, Meta, or open-source model ecosystems.
Cloud & DevOps: Experience with cloud platforms, Git, Docker, CI/CD, and production deployment workflows. Kubernetes and AWS experience are considered a plus.
Communication: Fluent English and strong communication skills, with the ability to explain technical ideas clearly and work effectively in a fast-moving team.
Additionally, the following will be considered a plus:
Experience in the maritime, shipping, logistics, or supply-chain industry.
Strong software engineering or backend platform background.
Experience with AWS services such as Lambda, ECS, EKS, S3, RDS, Bedrock, SageMaker, or CloudWatch.
Experience building AI agents, tool-calling systems, workflow automation, or internal AI platforms.
Experience with evaluation frameworks, LLM observability, guardrails, security, and compliance for AI systems.
Strong product mindset and ability to turn ambiguous business problems into practical technical solutions.

Benefits

Comp & perks

Attractive compensation package based on experience and skillset
30 days of paid annual leave
Comprehensive private health insurance coverage for your entire family
Hybrid way of work
Yoga classes, Life Coach, Running Coach and Kick-Boxing Sessions
Cool start-up environment (with swag, and much more)