AI Specialist

We are a technology company that started its journey in 2008. Our main headquarters is located in the picturesque city of Poznań, nestled by the beautiful Malta lake. For more than 16 years, we have been assisting companies in developing and implementing innovative fintech solutions. Leveraging our expertise in areas such as blockchain, online payments, and more, our clients can invent and develop cutting-edge solutions and services that keep them at the forefront of innovation.

As an AI Specialist, you will be responsible for designing, developing, deploying, and optimizing AI/ML models tailored for enterprise use-cases. You will work closely with engineering teams and business stakeholders to translate complex requirements into scalable, production-ready AI systems.

We're looking for someone with a strong software engineering background (Java, , Python) as well as hands-on experience with vector databases, LLMs, fine-tuning, and AI architecture.

We're not just building software. We own the product and guide the client on technical strategy, architecture, and best practices. If you thrive in environments where your opinion shapes the product, this is the right role for you.

AI Specialist

SKILLS: Python | Java | | AI | LLM | MLOps

B2B: PLN / Hour

LOCATION: POZNAŃ (Hybrid, 1x a week in office)

DURATION: LONG TERM

Key Duties and Requirements: A Roadmap to Your Professional Success

Scope of responsibilities:

• Build, train, fine-tune, and deploy AI and machine-learning models, including LLMs, for corporate and enterprise clients.

• Architect and integrate AI systems into existing backend environments (Java, , Python).

• Create pipelines for data preprocessing, feature engineering, model evaluation, and versioning.

• Implement and manage vector databases (Pinecone, Weaviate, Qdrant, Milvus) for RAG and knowledge systems.

• Evaluate model performance and continuously enhance accuracy, robustness, and latency.

• Collaborate with cross-functional teams to translate business requirements into working AI solutions.

• Develop internal AI tools, automation systems, and reusable frameworks for client projects.

• Ensure high standards of code quality, documentation, and scalability.

• Stay up to date with AI research, LLM capabilities, and MLOps best practices to drive innovation.

• Mentor team members and support building strong internal AI expertise.

Here's a set of skills we require:

• 5+ years of experience working with AI/ML systems in production.

• 10+ years of programming experience.

• Strong programming skills in Python, Java, and

• Proven experience with vector databases (Pinecone, Weaviate, Qdrant, Milvus).

• Hands-on experience in setting up, training, and fine-tuning AI/LLM models (OpenAI, Azure AI, Anthropic, local models).

• Experience building RAG systems, embeddings pipelines, and model orchestration.

• Familiarity with MLOps tools (Docker, CI/CD, model deployment, cloud services).

• Strong understanding of data structures, APIs, distributed systems, and microservices.

• Experience working in a startup-like environment (high ownership, fast-paced, autonomous).

• Excellent problem-solving and analytical abilities.

• Curiosity, eagerness to experiment, and a proactive approach to learning.

• Strong communication and cross-team collaboration skills.

Nice to have:

• Experience with on-premise AI deployments for corporate security needs.

• Knowledge of prompt engineering techniques and evaluation frameworks.

• Experience integrating AI into enterprise systems (SAP, Salesforce, ServiceNow).

• Contributions to open-source AI projects or research.

Navigating the Hiring Process: What does the recruitment process for that position look like?

1. Technical interview - during this stage, we conduct video call with one of our experts. We evaluate your technical knowledge and experience required for the open position by discussing, solving and live coding real problems in the field. Duration is approximately 60 minutes.

2. Meeting with DM – this is a short online conversation to better understand how you work within a team and your approach to project delivery, communication, and collaboration. Duration about 30 minutes.