AI Developer + Java

150 - 165 PLN/ godz./ godz.

SeniorOn-siteFull-time

#462460·Dodano 25 dni temu·2

Źródło: LinkGroup

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Tech Stack / Keywords

PythonRAGLLM PostgreSQL Redis Azure GCP Docker Kubernetes Java

Podsumowanie oferty

Lead the technical design, execution and production deployment of flagship AI/ML systems. Build RAG systems, vector database integrations and intelligent agents for complex financial datasets, using Python and its ML/AI ecosystem.

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 modern CI/CD pipelines.
Practical experience with TDD, BDD and automated testing.
Exceptional verbal and written English communication and presentation skills; able to influence cross-functional stakeholders at all levels.

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 and champion coding standards, testing methodologies and responsible AI best practices, including model fairness, transparency and governance.
Guide, unblock and elevate 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 to unlock value from complex financial datasets.
Translate business objectives into technical architecture and communicate technical strategies to technical teams and business leaders.

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