Senior Gen Ai
Skills
About This Role
Key Responsibilities
- Design, build, and optimize GenAI and agentic AI solutions for enterprise use cases.
- Develop and maintain scalable microservices and AI pipelines for production environments.
- Build and deploy machine learning models for fraud detection, compliance monitoring, and financial crime prevention.
- Implement Generative AI solutions, including synthetic data generation and advanced NLP applications.
- Deploy scalable ML systems capable of processing large-scale transactional data with improved operational efficiency.
- Optimize model performance through hyperparameter tuning and advanced evaluation techniques.
- Conduct A/B testing and performance analysis for ML-driven solutions.
- Develop production-grade, PEP8-compliant Python code focused on scalability, readability, and maintainability.
- Collaborate with cross-functional teams and communicate technical concepts effectively to non-technical stakeholders.
Required Skills & Experience
- Experience with advanced LLM techniques such as RAG, Graph RAG, AI Agents, and fine-tuning approaches.
- Strong hands-on experience with GenAI technologies and LLM ecosystems.
- Familiarity with both open-source and commercial LLMs, including models such as Llama, Mistral, Gemma, GPT, Claude, and Gemini.
- Expertise in Prompt Engineering, RAG pipelines, RAFT, and PEFT methods (LoRA, QLoRA, etc.).
- Strong proficiency in Python and GenAI/NLP frameworks.
- Experience with Generative Models including GANs, VAEs, and Transformers.
- Solid understanding of NLP tasks including:
Topic Modeling
- Exposure to cloud technologies, APIs, Docker, and vector databases such as Qdrant and PostgreSQL is a plus.
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