Generative AI Engineer
Core
Design, develop, and deploy advanced Generative AI solutions, including Multi-Agent Systems and RAG pipelines, for large-scale production environments.
Role type
Senior Generative AI Engineer
Builds
Scalable AI-powered products and solutions using AWS services and enterprise integrations
Domain
Generative AI, Large Language Models (LLMs), Vector Databases, Knowledge Graphs (via careerplan.io/jobs/15-007-9E-F6D-generative-ai-engineer-at-abra)
Deliverable
production ML models
Required skills
Python development, AWS AI/ML services (S3, Glue, Athena, SageMaker, Lambda, Bedrock), Generative AI frameworks (LangChain, LlamaIndex, Haystack), RAG pipeline design, Vector Database management, MLOps (CI/CD, Docker), API/Microservices integration
Preferred skills
Financial services domain knowledge, Graph databases (Neo4j, Amazon Neptune), MLOps platforms (Kubeflow, MLflow)
Technologies
AWS Bedrock, SageMaker, Lambda, Step Functions, Pinecone, Weaviate, ChromaDB, LangChain, LlamaIndex, Haystack, Docker, Git
Responsibilities
Lead end-to-end architecture and deployment of GenAI applications; Design and optimize RAG pipelines integrating LLMs with structured/unstructured data; Build and automate GenAI solutions on AWS; Lead POCs and evaluate emerging GenAI technologies; Integrate AI solutions with enterprise systems via APIs; Implement MLOps processes for reliability and scalability
Seniority
Senior, hands-on IC
