AI engineer in enterprise solutions

Haptiq; Warszawa; Presencial; PLN 180.000 - 260.000; Jornada completa

Descripción de la vacante

Haptiq ищет инновационного AI-инженера в команду AI, чтобы спроектировать, прототипировать и внедрять передовые AI-системы, включая RAG-пайплайны, MCP-сервисы и агентные рабочие процессы. Вы будете тесно сотрудничать с Python-разработчиками и инженерами MLOps, переводя идеи в рабочие продукты.

Обязанности включают проектирование моделей, настройку векторного поиска и разработку промптов для задач чат-ботов, суммаризации и информационного извлечения.

Formación

• Strong Python development skills with clean, scalable code.
• Hands-on experience with LLMs and agent frameworks.
• Solid understanding of RAG architecture and vector search concepts.
• Experience building multi-step agentic workflows and reasoning systems.
• Familiarity with AI performance metrics and monitoring.
• Knowledge of model drift, latency, hallucinations, explainability.
• Curious, experimental mindset for testing new tools.
• Strong ML fundamentals: regression, classification, clustering, evaluation.
• Experience with ML frameworks: PyTorch, TensorFlow, or scikit-learn.
• Bachelor's degree in CS or equivalent preferred.

Responsabilidades

• Design, prototype, and iterate on AI models, RAG pipelines, MCP services, and agentic reasoning systems.
• Develop AI-powered services using LangChain, LangGraph, CrewAI, LlamaIndex, Haystack.
• Train and evaluate ML models for real-world production use cases.
• Deploy, monitor, and maintain ML models in production, handle drift and retraining.
• Build and optimize prompts for chat, summarization, information extraction, and decision support.
• Integrate vector databases to optimize vector search workflows.
• Collaborate with developers to define service interfaces and APIs.
• Monitor AI system performance and evaluation metrics; stay current with AI observability.

Conocimientos

Python development

LLMs and agent frameworks

RAG architecture

Vector search concepts

Experimentation mindset

Model evaluation & monitoring

ML fundamentals

PyTorch / TensorFlow / scikit-learn

System design

Prompt optimization awareness

Educación

Bachelor's degree in Computer Science or equivalent

Herramientas

LangChain

LangGraph

CrewAI

LlamaIndex

Haystack

Chroma

FAISS

Pinecone

Qdrant

Descripción del empleo

Описание: Haptiq is an AI-native enterprise solutions company helping organizations transform complex data, workflows, and business processes into scalable technology-driven operations. We’re looking for an innovative AI Engineer to join our AI team and help design, prototype, and operationalize advanced AI systems, including Retrieval-Augmented Generation (RAG) pipelines, MCP services, and agentic workflows. You’ll work closely with Python Developers and MLOps Engineers to bring AI-powered features from concept to production.

Задачи:

Design, prototype, and iterate on AI models, RAG pipelines, MCP services, and agentic reasoning systems. Develop AI-powered services using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, and Haystack. Design, train, and evaluate machine learning models (supervised, unsupervised, and reinforcement learning) for real-world production use cases. Perform data preprocessing, feature engineering, and dataset curation to improve model performance and robustness. Experiment with model architectures, hyperparameter tuning, and optimization techniques to achieve performance targets. Implement model validation strategies, including cross-validation, A/B testing, and offline/online evaluation pipelines. Deploy, monitor, and maintain ML models in production, including handling model drift, retraining, and versioning. Build and optimize prompts for AI-driven tasks like chat, summarization, information extraction, and decision support. Integrate and tune vector databases (e.g., Chroma, FAISS, Pinecone, Qdrant) to optimize vector search workflows. Collaborate with Python Developers to define service interfaces, APIs, and operational requirements. Implement task decomposition, memory management, and tool-use strategies within agentic systems. Monitor AI system performance, operational risks, and prompt evaluation metrics. Stay current with emerging AI frameworks, architectures, and best practices in AI observability and evaluation.

Требования:

Strong Python development skills with an emphasis on clean, scalable, and modular code. Hands-on experience working with LLMs and agent frameworks. Solid understanding of RAG architecture, vector search concepts (cosine similarity, MMR, late interaction), and system design. Experience building multi-step agentic workflows and reasoning systems. Familiarity with AI performance metrics, model drift detection, and operational monitoring. Awareness of AI limitations, including latency, hallucination risks, and explainability challenges. A curious, experimental mindset with a passion for testing emerging AI tools and frameworks. Strong foundation in machine learning fundamentals, including regression, classification, clustering, and model evaluation techniques. Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn for model development and experimentation. Будет плюсом: Experience with prompt optimization tools is a plus; Bachelor's degree in Computer Science or equivalent - preferred.

Условия:

We value creative problem solvers who learn fast, work well in an open and diverse environment, and enjoy pushing the bar for success ever higher. We do work hard, but we also choose to have fun while doing it.