Related skills
python prompt engineering rag generative ai llm📋 Description
- Contribute to architecture and production-ready GenAI/ML systems.
- Build end-to-end GenAI features: APIs, model integration, monitoring.
- Optimize LLMs for business planning: prompt engineering and RAG.
- Create conversational interfaces and agentic workflows for planning tasks.
- Implement evaluation frameworks to measure accuracy, latency, and satisfaction.
- Design APIs exposing AI capabilities to Anaplan and third-party integrations.
🎯 Requirements
- Extensive hands-on experience in AI/ML or related engineering domains.
- End-to-end model lifecycle development; deploying/maintaining ML models in production.
- Strong knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience in fine-tuning LLMs for domain-specific enterprise applications.
- Experience with MLOps and LLMOps for scalable deployments.
- Worked with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Desirable: vector databases (Pinecone, Weaviate, Qdrant) and embedding models.
🎁 Benefits
- Winning Culture focused on innovation and customer success.
- Commitment to diversity, equity, inclusion and belonging.
- Opportunity to work on greenfield AI projects with global impact.
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