AI Engineer

AI Engineer

myPOS

Remote, Bulgaria

As we are expanding our team, we’re looking for AI engineer to help us make a real difference in the Fintech industry. Ready to join us and shape the future of payments? Let’s make it happen!

About the role:

As an AI Engineer, you'll design, build, and operate production-grade AI/ML systems - from agentic applications and MCP-powered tools to the underlying MLOps infrastructure and data foundations that make them reliable at scale. You'll sit at the intersection of applied AI, DevOps/MLOps, and data engineering, taking systems from prototype to production and keeping them healthy once they're there. Your work will power intelligent products and internal automation across the company, and will help shape how the organisation safely adopts AI at scale.

What you’ll do:

• Design and build agentic systems: single agents, multi-agent orchestration, and sub-agent patterns for complex workflows (planner/executor, supervisor/worker, hierarchical task decomposition)
• Develop MCP (Model Context Protocol) servers and tools that expose internal systems, datasets, and actions to LLM-powered applications in a safe, governed, and reusable way
• Implement retrieval systems (RAG, hybrid search, graph-based retrieval) including chunking, embedding, re-ranking, and context-assembly strategies
• Build and maintain MLOps automation: CI/CD for models and agents, environment management, artifact handling, and versioning of prompts, models, data, and code
• Implement observability for AI systems: tracing, token/latency/cost metrics, quality and drift monitoring, alerting, and incident response
• Build and maintain data pipelines for ingestion, transformation, and export across multiple sources and destinations
• Expose well-modelled, governed datasets and APIs that agents, tools, and downstream consumers can rely on
• Ensure secure data handling and compliance with relevant data protection standards and internal policies
• Contribute to documentation, standards, and continuous improvement of the data platform and engineering processes

This role is perfect for you if you have:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience)
• 5+ years of Data or ML Engineering experience, with at least 3 years shipping AI or ML systems to production.
• Strong Python skills (typed code, async, testing) and solid SQL fluency.
• Hands-on experience building agentic applications with frameworks such as LangGraph, LlamaIndex, CrewAI, or the Anthropic/OpenAI Agents SDKs - including tool use, memory, and multi-step reasoning patterns.
• Practical experience with MCP or comparable tool/function-calling protocols; comfortable designing tool schemas and sub-agent boundaries.
• Experience with RAG architectures, vector stores (e.g. pgvector, Pinecone, Weaviate), and embedding models
• Familiarity with at least one major cloud provider (GCP, AWS, Azure) and deploying data solutions in the cloud
• Strong DevOps fundamentals: CI/CD (GitHub Actions, Cloud Build, or similar), IaC (Terraform), containerisation (Docker), and orchestration (Kubernetes or serverless equivalents)
• Comfortable building and maintaining data pipelines with orchestrators (Airflow/Composer, Dagster) and distributed engines (Spark, BigQuery)
• Strong troubleshooting mindset: ability to debug issues across data, infra, pipelines, and deployments
• Collaborative mindset and clear communication across engineering, analytics, and business stakeholders

Nice to have:

• Strong GCP experience and ecosystem knowledge: Vertex AI (Agent Engine, Model Garden, Pipelines, Endpoints), Cloud Run, BigQuery, Composer, Dataproc, Cloud Run, Dataplex, Cloud Storage
• Experience with data governance concepts: access control, retention, data classification, auditability, and compliance standards
• Model monitoring experience: drift detection, data quality issues, performance degradation, bias checks, and alerting strategies