Artificial Intelligence / Machine Learning Engineer

Engenious

AI/ML Engineer developing document-processing pipelines and autonomous AI agents at Engenious. Collaborating with global teams using modern tools and AWS services for data handling.

Posted 7/11/2026contractRemote • 🇵🇱 PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing document-processing pipelines using ML/LLM technologies, with strong proficiency in Python and experience in building microservices. Capable of optimizing AI systems for performance and accuracy while utilizing AWS services and AI-assisted development tools.

Highest-signal resume keywords

Python Microservices DevelopmentML/LLM-Based ExtractionAWS Services (ECS, SQS, SNS, RDS, S3)Prompt Engineering and Evaluation MetricsAI-Assisted Development Tools (Claude Code, Cursor)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonDocument-Processing PipelinesOCR ToolsLLM Providers (OpenAI, Claude, Gemini, Llama, Grok)Data-Processing Libraries (Pandas, NumPy)DockerEvaluation Metrics (Accuracy, Precision, Recall, F1 Score)Asynchronous ProcessingAgentic WorkflowsPrototyping and R&D

Tools & Technologies

AWS (ECS, SQS, SNS, RDS, S3, OpenSearch, CloudWatch)AI-Assisted Development Tools (Claude Code, Cursor)

Industry Keywords

Machine LearningArtificial IntelligenceData ProcessingMicroservicesEvaluation Datasets

Tech Stack

Tools & technologies

AWSDockerMicroservicesNumpyPandasPython

About the role

Key responsibilities & impact

Develop document-processing pipelines with ML/LLM-based extraction and agentic workflows
Build and extend Python microservices for document ingestion, classification, extraction, validation, and post-processing
Develop autonomous AI agents using tool calling, structured outputs, and advanced reasoning
Prepare evaluation datasets and define ground-truth target values for extracted data
Evaluate extraction results, analyze failures, and improve prompts, schemas, and pipeline logic
Build automated testing and regression frameworks for prompts, models, agents, and extraction workflows
Optimize AI systems for accuracy, latency, throughput, reliability, and cost
Work with asynchronous processing infrastructure using AWS services such as ECS, SQS, SNS, RDS, and S3
Use AI-assisted development tools such as Claude Code, Cursor, and similar solutions while following engineering, testing, and code-review best practices
Prototype new AI solutions in collaboration with engineering teams

Requirements

What you’ll need

At least 3 years of AI/ML experience and 6+ years of overall experience
Strong proficiency in Python
Experience building Python microservices and data-processing pipelines
Experience with OCR tools and document-processing platforms
Practical experience with LLM-based extraction, classification, reasoning, and structured outputs
Experience working with LLM providers and model families such as OpenAI, Claude, Gemini, Llama, and Grok, including multimodal models
Strong knowledge of prompt engineering, embeddings, semantic search, tool calling, and agentic workflows
Experience preparing evaluation datasets and defining expected target values
Understanding of evaluation metrics such as accuracy, precision, recall, F1 score, and completeness with AI safety guardrails, privacy controls, and prompt-injection protection
Experience with AWS services, particularly ECS, SQS, SNS, RDS, S3, OpenSearch, and CloudWatch
Experience with Docker, message queues, retry mechanisms, and distributed processing
Experience with data-processing libraries such as Pandas and NumPy
Practical experience with AI-assisted development tools such as Claude Code or Cursor
Prototyping, R&D, or hackathon experience
English proficiency at B2 level or higher.

Benefits

Comp & perks

Flexible & remote job
Paid vacation and sick leave
Development opportunities in any IT direction
Fun and friendly team
Personal professional growth
Up to 100% reimbursement of participation in core courses and conferences