AI engineer in enterprise solutions

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.

• 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.

• 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

• 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.