Senior AI Engineer

1000 - 1500 PLN/ dzień./ dzień.B2BB2B (netto)

SeniorHybryda·WarszawaFull-time·B2B

#463197·Dodano 2 dni temu·1

Źródło: justjoin.it

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Tech Stack / Keywords

AIMachine Learning PythonRAGLLMData EngineeringAzure Databricks Langgraph

Podsumowanie oferty

Build AI-powered services and data infrastructure for a WealthTech platform, turning financial data into products for intelligent applications. The role combines backend and data engineering with Python, LLMs, and RAG solutions.

Wymagania

4+ years of professional software engineering experience, with a strong background in backend, data, machine learning, or AI engineering.
Experience in FinTech, WealthTech, banking, or financial data.
Strong Python programming skills.
Experience building production-grade backend applications and APIs.
Hands-on experience building applications with modern LLMs, including AI agents, agentic workflows, RAG architectures, and orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
Experience with prompt engineering, model evaluation, and testing AI applications.
Experience working with databases.
Understanding of modern data engineering concepts and ETL/data pipelines.
Experience working with cloud platforms, preferably Azure.
Knowledge of REST APIs and distributed systems.
Strong problem-solving skills and ability to work independently.
Very good English communication skills.

Nice to have:

Experience with MLOps, model monitoring, evaluation, and observability tools such as Langfuse or MLflow.
Knowledge of Azure AI, Azure OpenAI, Databricks, Microsoft Fabric, or similar technologies.
Experience with event-driven architectures and messaging systems.
Understanding of AI governance, security, privacy, and regulated environments.
Experience working in startups or building products from scratch.

Obowiązki

Design, build, and maintain AI-powered services and backend applications.
Develop pipelines to ingest, validate, normalize, enrich, and transform financial data from multiple sources.
Build and optimize applications based on LLMs, AI agents, RAG, and orchestration workflows.
Develop APIs and services that expose AI-ready financial data objects.
Design prompt engineering strategies, model evaluation, benchmarking, and observability.
Evaluate and optimize AI solutions for accuracy, reliability, latency, token usage, and cost.
Translate business requirements into scalable technical solutions with Product and Engineering teams.
Contribute to scalable cloud-native architecture and backend services.
Write clean, maintainable, well-tested production code.
Participate in code reviews, architecture discussions, and continuous improvement initiatives.
Support deployment, monitoring, troubleshooting, and performance optimization of AI applications.
Evaluate new models, AI technologies, frameworks, and best practices.

Benefity

Access to private medical care (Medicover) and a Multisport card.
Integration events, offsites, and regular team lunches.
Flexible working hours.

Opieka zdrowotna

Karta sportowa

Spotkania integracyjne

Elastyczne godziny

Inne informacje

The hybrid setup requires a minimum office presence of 8 days per quarter, or more depending on team needs.

WealthArc

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