AI Developer + Java

150 - 165 PLN/ godz./ godz.B2BB2B (netto)

SeniorHybryda·KrakówFull-time·B2B

#462539·Dodano 3 dni temu·0

Źródło: nofluffjobs.com

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Tech Stack / Keywords

AIPython ML LLM Deep learning NLPRAGRelational databasePostgreSQL RedisPUBMicroservices REST API gRPCAPICloudAzure GCP Docker KubernetesCI/CD PipelinesAzure DevOpsJenkinsTDDBDDAutomated testingJava

Podsumowanie oferty

Lead the technical design, execution, and production deployment of flagship AI/ML systems for complex financial datasets. Build production-ready solutions using Python, LLMs, RAG, and cloud platforms.

Wymagania

Proven experience in a senior or lead software engineering capacity, including guiding technical projects and mentoring teams.
Deep expertise in Python and its ML/AI ecosystem.
Expert understanding of LLM architectures, deep learning, and NLP, with hands-on experience fine-tuning models on domain-specific data.
Practical mastery of RAG, advanced prompt engineering, and designing agentic architectures.
Hands-on experience with relational databases such as PostgreSQL, vector databases, key-value stores such as Redis, and Pub/Sub event messaging.
Strong command of microservices, REST/gRPC API design, concurrency models, and observability.
Proficiency with Azure and/or GCP, containerization with Docker and Kubernetes, and CI/CD pipelines.
Practical experience in TDD, BDD, and automated testing.
Exceptional verbal and written English communication and presentation skills, including the ability to influence cross-functional stakeholders.

Nice to have:

Familiarity with Java for middleware and enterprise integrations.

Obowiązki

Technical Leadership & Strategy:

Lead the technical design, execution, and production deployment of core AI/ML systems and flagship platform capabilities.
Co-drive long-term technical strategy by prototyping advanced RAG pipelines, agentic workflows, LLM fine-tuning, and model optimization techniques.
Establish coding standards, testing methodologies, and responsible AI practices, including model fairness, transparency, and governance.
Guide, unblock, and mentor fellow engineers.

Software & AI Systems Engineering:

Design, write, and maintain robust, testable, reusable, and well-documented production code.
Build RAG systems, vector database integrations, and intelligent agents for complex financial datasets.
Translate business objectives into technical architecture and communicate technical strategies to technical teams and business leaders.

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