Sr. AI Software Engineer

5+ years of professional experience in Applied AI Engineering, ML Engineering, or a related role. Advanced proficiency in Python and hands-on experience with AI/ML frameworks (e.g., LangChain, LlamaIndex, CrewAI, PyTorch). Expertise with data and ML libraries (e.g., Pandas, spaCy). Demonstrated success deploying and maintaining applications powered by LLMs in production. Deep, hands-on experience designing, building, and optimizing RAG pipelines. Expertise in vector databases (e.g., Qdrant, Pinecone, Weaviate), embedding strategies, and chunking techniques. Demonstrable experience with modern evaluation techniques for multi-step AI agents. Demonstrable skill in designing, testing, and optimizing complex prompts and few-shot examples. Experience in fine-tuning foundation models for specific downstream tasks. Advanced proficiency with API-driven frameworks for accessing and serving self-hosted foundation models (e.g., AWS SageMaker/Bedrock, Databricks Model Serving, TGI, vLLM). Proven ability to optimize AI systems for low latency and high throughput. Intermediate proficiency with MLOps tooling (e.g., MLFlow, Arize) and CI/CD best practices for AI systems. Bachelor's Degree in Computer Science, Engineering, Statistics, or a related field (or equivalent practical experience).

Design, build, and deploy scalable, production-grade applications using foundation models and advanced AI techniques. Engineer robust Retrieval-Augmented Generation (RAG) pipelines and multi-step agentic workflows. Establish and manage rigorous evaluation frameworks for complex AI agents. Craft, test, and manage sophisticated prompt chains and templates. Develop resilient serving architectures that integrate Large Language Models (LLMs) with enterprise systems. Develop and maintain sophisticated MLOps and CI/CD pipelines for generative AI. Translate customer challenges into innovative AI features.