Pre-Sales Engineer (AI & Big Data)
New
Warszawa, Krucza 50, Kraków, Aleksandra Lubomirskiego 20, Wrocław, Świdnicka 40, Katowice, -, Gdańsk, -, Warszawa, Country code: PLFull-TimeSenior
Salary21,000 - 33,000 PLN per month
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Job Details
- Languages
- Excellent English (at least C1 level).
- Required Skills
- PythonArtificial IntelligenceMachine LearningData engineeringData scienceDatabricksLLMGenerative AI
Requirements
- Undergraduate degree in Computer Science, Data Science, Engineering, or equivalent hands-on experience.
- Proven experience in technical roles such as AI/ML products, data platforms, or solution engineering.
- Foundational understanding of public cloud platforms (AWS, Azure, GCP) with experience deploying cloud-based AI solutions.
- Strong foundational understanding of AI/ML workflows from preprocessing to deployment.
- Familiarity with LLM-based applications, including embeddings, vector databases, and orchestration frameworks like LangChain or LlamaIndex.
- Working knowledge of MLOps and orchestration tools such as MLflow, Airflow, Kubeflow, Vertex AI, or SageMaker.
- Proficiency in Python and AI/ML libraries like pandas, scikit-learn, PyTorch, or TensorFlow.
- Understanding of modern data architectures including ETL/ELT, big data processing, and cloud platforms like Databricks or Azure Synapse.
- Excellent English (at least C1 level).
- Strong communication skills for simplifying complex technical concepts for diverse audiences.
- Excellent time management and multitasking ability.
Responsibilities
- Serve as a technical advisor during pre-sales and early engagement stages, helping clients understand what’s possible with AI/LLMs and modern data platforms.
- Lead or support technical discovery sessions, clarifying business problems, identifying solution patterns, and assessing feasibility.
- Design and communicate solution architectures, including LLM integrations, RAG, vector databases, and modern cloud data architectures.
- Create and deliver technical PoCs, PoVs, demo narratives, and early prototypes to support proposals.
- Contribute to internal R&D by evaluating emerging AI tools, libraries, and frameworks.
- Collaborate with sales, delivery, and engineering teams to ensure a smooth transition from pre-sales to project implementation.
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