Job description
As a Middle-Level AI Engineer, you will be a key contributor to the development and optimization of our AI Agent systems. You will bridge the gap between conceptual architecture and practical implementation, taking ownership of specific modules within our orchestration engine and multi-agent frameworks. You will be responsible for building reliable, scalable features that allow AI Agents to reason, interact with tools, and collaborate effectively. You are expected to work with a high degree of independence while collaborating with senior architects to refine the system's capabilities.Key Responsibilities
Feature Ownership: Independently design and implement core features for AI Agents, including tool-use capabilities, function calling, and complex task-reasoning logic.
Workflow Implementation: Build and refine sophisticated workflows within our orchestration engine, ensuring efficient task decomposition, execution, and error handling.
Advanced LLM Integration: Go beyond basic API calls to optimize LLM performance through advanced prompting techniques (ReAct, Chain-of-Thought), fine-tuning context window management, and handling embeddings.
ML Model Application: Integrate and fine-tune traditional machine learning models for tasks such as detection, prediction, and classification to enhance agent decision-making and data processing.
Agent Communication \& Memory: Implement and maintain protocols for agent-to-agent communication and memory persistence, ensuring data consistency and state management across long-running tasks.
Performance Optimization: Monitor agent performance, identify latency bottlenecks in LLM calls, and implement solutions to improve system speed and cost-efficiency.
Code Quality \& Peer Review: Maintain high code standards through rigorous testing and peer reviews. Assist in the technical growth of junior engineers through mentorship and documentation.
Prototyping \& Iteration: Translate research findings and senior-level architectural designs into functional prototypes, quickly iterating on agentic design patterns to prove product viability.
Your skills and experience
Required Skills and Qualifications
Education: Bachelor’s degree in Computer Science, Artificial Intelligence, or a related technical field.
Experience: 3+ years of professional software engineering experience, with at least 1-2 years of hands-on experience building and deploying AI/LLM applications.
Machine Learning Knowledge: Solid understanding of core ML concepts and practical experience implementing models for classification, object detection, or predictive analytics using libraries like Scikit-Learn, PyTorch, or TensorFlow.
Python Proficiency: Expert-level proficiency in Python, including experience with asynchronous programming (Asyncio) and building production-grade APIs (FastAPI/Flask).
AI Frameworks: Strong experience with modern orchestration frameworks such as LangChain, LlamaIndex, or Haystack.
RAG \& Vector Data: Solid understanding of Retrieval-Augmented Generation (RAG) patterns and experience working with vector databases (e.g., Pinecone, Weaviate, or Milvus).
Engineering Best Practices: Deep familiarity with Git, Docker, CI/CD pipelines, and cloud environments (e.g., AWS, Azure, or SAP BTP).
Analytical Thinking: Ability to take semi-structured requirements and deliver a structured technical solution with minimal supervision.
Preferred Qualifications
Multi-Agent Systems: Familiarity with multi-agent orchestration libraries (e.g., Microsoft AutoGen, CrewAI) or custom state-machine logic.
LLM Observability: Experience using LLM monitoring and evaluation tools (e.g., LangSmith, Arize Phoenix, or Weights \& Biases).
Infrastructure: Knowledge of deploying AI agents in scalable, distributed environments and managing model inference costs.
Community Engagement: Active involvement in the AI open-source community or a portfolio of personal projects involving autonomous agents.
Why you'll love working here
15 days of annual leaves
Competitive salary (+13-month salary include)
Health insurance, social insurance according to the government regulations
PVI Healthcare Insurance
Have a chance to work in an international, friendly, open environment
Annual Travel opportunity