Senior Agentic AI, Adaptive RAG engines Engineer
US Company is searching for a couple of Senior AI Engineers into a complex, enterprise-level project for building sophisticated Agentic Systems, Adaptive RAG engines, capable of autonomous research to solve complex, real-world problems. Interesting project with cutting edge technologies, distributed team, full-time, an official contract. Remote work, flexible schedule.
Brief project description:
- The product is SaaS, which allows multiple functions for sustainability & operational risk management. The project is dedicated for developing of AI Center of Excellence.
Key areas of responsibility:
- Platform Engineering: Build and enhance scalable, reusable AI services (e.g., "Adaptive RAG Engine," "Text-to-SQL Service," and "Agentic Runtime") that product teams can easily integrate.
- Technical Contribution: Collaborate with principal engineers and architects. Participate in code reviews, write robust tests, and help drive the adoption of engineering best practices (CI/CD for AI, evaluation).
- Agentic Innovation: Develop and implement multi-agent systems capable of complex reasoning, planning, tool use, and self-correction (using frameworks like LangGraph or PydanticAI or Databrics' Agent Brics).
- Data Engineering: Load datasets and knowledge sources from external systems. Shape and transform data to optimize it for Hybrid or Semantic Search, providing the best possible knowledge context to LLMs.
- Production Readiness: Help move prototypes to production with a focus on latency, cost optimization, and reliability. Implement robust evaluation pipelines (LLM-as-a-Judge) to measure quality and prevent regression.
- Collaboration & Enablement: Partner with product teams to implement their AI roadmaps. Translate business requirements into concrete technical implementations.
Required skills (at least one or more for each category):
- Professional Experience: At least 5 years of professional experience in software development or Data Science.
- Education: Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, Physics, or a related natural science field.
- Python Expertise: At least 5 years of hands-on experience with Python, writing clean, maintainable, and production-ready code.
- Strong Software Engineering Foundation: distributed systems, API design (FastAPI), and cloud architecture.
- Data Engineering Expertise: Data Engineering and Big Data (DeltaLake, Databrics etc.) experience are a big plus.
- GenAI Engineering Experience: Hands-on experience building production RAG systems. Chunking strategies, hybrid search (dense + sparse), re-ranking, and context management.
- Agentic Workflow Experience: You have experience building systems where LLMs use tools, maintain state, and execute multi-step plans. You are familiar with the challenges of loops, recursion, and hallucination mitigation.
Tech Stack:
- Languages: Python, TypeScript
- AI Frameworks: LangChain/LangGraph, Pydantic AI, MosaicAI
- Models: Azure OpenAI (GPT-4o, o1), Open Source LLMs (Llama 3, Mistral)
- Infrastructure: Azure AI Search, Azure Container Apps, Delta Lake, Vector Databases like Databrics Vector Search.
Work conditions:
- Distributed team, remote work.
- Kanban or scrum approach, 5-6 team members / team.
- Full-time (40 hours per week).
- Official contract: salary, sick-leave days, holidays, vacations.
Hiring process:
- Step 1 - preliminary interview (main questions) - 20 mins
- Step 2 - internal tech interview (tech questions) - 40-50 mins
- Step 3 - tech interview with team leader and architect - 1 hour
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$4500-7500
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