AI Agent Middle/Senior Developer
⚲ Warszawa, Wrocław
Do uzgodnienia
Wymagania
- Python
- RAG
- CRAG
- GraphRag
- Langchain
- Langgraph
- CrewAI
- Agentic Tools
Opis stanowiska
We are looking for a skilled AI Agent Developer to join our AI team. You should have proven production experience with AI systems and a strong interest in learning and growing with modern agent technologies.
Requirements:
• Strong Python skills and proven production experience with Agentic ecosystems
• Embeddings & Vector search
• Prompt & Context engineering
• RAG, CRAG, GraphRAG
• LangChain, LangGraph, CrewAI
• Agent's testing & verification
• Agentic Tools and skills
• AI-assisted coding models & tools
• Strong analytical and problem-solving mindset
• Ability to clearly communicate findings and trade-offs
• Ownership of tasks from research to implementation
• Curiosity and willingness to explore new approaches
• Level of English enough for efficient technical and business communication with native speakers
Nice to have:
• Autonomous Agents & Deep Agents
• Model types and capabilities (Thinking, Multimodal models)
• LLMOps
• GenAI Observability
• Memory management & Prompt caching
• Model Governance & Data Governance (Responsible AI)
• Basics knowledge of Cloud infrastructure
• Agentic patterns
• Integration mechanics (MCP, AA-protocol)
• Basic understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation; Overfitting, regularization, cross-validation
• Knowledge of statistical methods and probability theory
Responsibilities:
• Develop, implement, and optimize AI agents capable of autonomous decision‑making, reasoning, and tool‑usage in real‑world scenarios
• Build and maintain pipelines for agent planning, memory, retrieval, and multi‑step task execution
• Integrate LLMs, vector stores, APIs, and external tools to enable complex agent behaviors
• Design and refine prompting strategies, reasoning chains, and agent policies to improve reliability and accuracy
• Implement evaluation frameworks for agent performance, safety, and robustness across diverse tasks
• Monitor agent behavior in production, troubleshoot failures, and continuously improve quality of outputs
• Optimize inference pipelines for speed, cost efficiency, and model/tool selection
We offer:
• Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota
• Competitive compensation that depends on your qualification and skills
• Career development system with clear skill qualifications
• Flexible working hours aligned to your schedule
• Options to work remotely
Requirements:
• Strong Python skills and proven production experience with Agentic ecosystems
• Embeddings & Vector search
• Prompt & Context engineering
• RAG, CRAG, GraphRAG
• LangChain, LangGraph, CrewAI
• Agent's testing & verification
• Agentic Tools and skills
• AI-assisted coding models & tools
• Strong analytical and problem-solving mindset
• Ability to clearly communicate findings and trade-offs
• Ownership of tasks from research to implementation
• Curiosity and willingness to explore new approaches
• Level of English enough for efficient technical and business communication with native speakers
Nice to have:
• Autonomous Agents & Deep Agents
• Model types and capabilities (Thinking, Multimodal models)
• LLMOps
• GenAI Observability
• Memory management & Prompt caching
• Model Governance & Data Governance (Responsible AI)
• Basics knowledge of Cloud infrastructure
• Agentic patterns
• Integration mechanics (MCP, AA-protocol)
• Basic understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation; Overfitting, regularization, cross-validation
• Knowledge of statistical methods and probability theory
Responsibilities:
• Develop, implement, and optimize AI agents capable of autonomous decision‑making, reasoning, and tool‑usage in real‑world scenarios
• Build and maintain pipelines for agent planning, memory, retrieval, and multi‑step task execution
• Integrate LLMs, vector stores, APIs, and external tools to enable complex agent behaviors
• Design and refine prompting strategies, reasoning chains, and agent policies to improve reliability and accuracy
• Implement evaluation frameworks for agent performance, safety, and robustness across diverse tasks
• Monitor agent behavior in production, troubleshoot failures, and continuously improve quality of outputs
• Optimize inference pipelines for speed, cost efficiency, and model/tool selection
We offer:
• Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota
• Competitive compensation that depends on your qualification and skills
• Career development system with clear skill qualifications
• Flexible working hours aligned to your schedule
• Options to work remotely
🔍 Dekoder Ogłoszenia
🔴
proven production experience with AI systems
Oczekuje się, że kandydat faktycznie wdrażał i utrzymywał systemy AI w środowisku produkcyjnym, a nie tylko eksperymentował.
🔴
strong interest in learning and growing with modern agent technologies
Może oznaczać, że technologie są nowe i niedojrzałe, a firma oczekuje, że kandydat będzie aktywnie uczestniczył w ich rozwoju i rozwiązywaniu problemów.
🔴
Ownership of tasks from research to implementation
Kandydat będzie odpowiedzialny za cały cykl życia zadania, od początkowego badania po finalne wdrożenie, co może oznaczać dużą samodzielność, ale też brak wsparcia.
🟡
Ability to clearly communicate findings and trade-offs
Oczekuje się, że kandydat potrafi nie tylko rozwiązywać problemy, ale także jasno tłumaczyć złożone kwestie techniczne i decyzyjne, co może być kluczowe w interakcji z mniej technicznymi interesariuszami.
🟡
Level of English enough for efficient technical and business communication with native speakers
Wymagany jest bardzo wysoki poziom biegłości językowej, umożliwiający swobodną i precyzyjną komunikację w kontekście biznesowym i technicznym.