Senior AI Engineer

Data & Model Optimization

Cross-Functional Collaboration & Innovation

What We’re Looking For

Minimum Qualifications

• LLMs & RAG: Proven experience designing and deploying systems using models like GPT, Claude, Gemini, or similar, including Retrieval-Augmented Generation (RAG) pipelines and contextual retrieval systems.
• AI Agents & Multi-Agent Systems: Hands-on experience with Crew.ai, LangChain, LangGraph, or similar frameworks to build orchestrated agentic workflows.
• Fine-Tuning & Context Engineering: Expertise in supervised fine-tuning (SFT), LoRA, or custom dataset adaptation for domain-specific tasks.
• Programming & Frameworks: Proficiency in Python, GO, and AI/ML libraries such as PyTorch, TensorFlow, or JAX.
• AI Infrastructure: Experience designing scalable, production-ready AI systems in AWS, GCP, or Azure, with a deep understanding of vector databases, model serving, and inference optimization.
• Observability & Monitoring: Familiarity with LangSmith, LangFuse, or equivalent tools for tracking, debugging, and evaluating LLM performance.
• API Integration: Expertise in integrating AI systems with RESTful APIs and internal platforms to create seamless, usable products.

Preferred Qualifications

• Experience using LlamaIndex, Hugging Face, or similar open-source frameworks.
• Strong understanding of context optimization, embedding strategies, and knowledge retrieval.
• Familiarity with MLOps, CI/CD pipelines, and production deployment best practices.
• Prior experience in fintech, payments, or other data-intensive and regulated industries.
• Analytical rigor and ability to translate business objectives into measurable AI outcomes.