Mid AI Engineer

hfm • Greece

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AI Summary

Build and ship internal AI services end-to-end, including data pipelines, models, and APIs. Develop asynchronous REST APIs and microservices in FastAPI on Kubernetes, implementing retrieval pipelines and training workflows. Requires 3+ years of backend experience, proficiency in Python and FastAPI, and practical experience with LLM application patterns.

Key Highlights

End-to-end development of AI services from data pipeline to API deployment

Implementation of retrieval pipelines using PostgreSQL and pgvector

Integration of agent tools and Model Context Protocol (MCP) endpoints

Key Responsibilities

Build and ship internal AI services end to end — from the data pipeline through the model to the API other teams call — working within the team's established architecture.

Develop asynchronous REST APIs and microservices in FastAPI, deployed on Kubernetes, to serve models and orchestrate agent tool calls.

Implement retrieval pipelines over PostgreSQL and pgvector — chunking, embedding, indexing and retrieval tuning — and measure them against a held-out evaluation set.

Build and maintain training pipelines covering data preparation, fine-tuning, evaluation and model registration, promoting a new model only when it measurably beats the one in production.

Integrate agent tools and Model Context Protocol (MCP) endpoints, ensuring each tool enforces its own access controls rather than relying on the model to do so.

Write the evaluation sets, structural output checks and drift monitoring that prove a model works before release and keep proving it afterwards.

Instrument services with structured logging, Prometheus metrics and OpenTelemetry tracing, so that failures can be diagnosed rather than guessed at.

Review the work of junior engineers and trainees, pair with them on delivery, and contribute to the team's engineering and documentation standards.

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Technical Skills Required

Python FastAPI PostgreSQL

Benefits & Perks

Hybrid Work Model (2 days working from home)

Monthly Food Vouchers

Comprehensive Health & Life Insurance

Summer Short Fridays (August)

Additional Paid Annual Leave

Birthday Leave

Udemy Business access

Referral Bonus Program

Visa Sponsorship

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Nice to Have

Experience running vector search in production (pgvector, OpenSearch, Qdrant or similar).

Exposure to multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen, LlamaIndex) or to the Model Context Protocol.

Experience with model registries and deployment workflows (MLflow or equivalent), or with serving open-weight models (e.g., vLLM).

Familiarity with analytical data stores such as ClickHouse, and with observability tooling (OpenTelemetry, Grafana, Langfuse).

Familiarity with FinTech platforms, FX trading, or financial services operations.

Job Description

is an internationally acclaimed multi-asset broker, delivering cutting-edge trading tools, platforms, and conditions to traders worldwide. We are committed to innovation, transparency, and excellence in the financial markets.As we continue to expand, we are seeking a driven and strategic to join our team.

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