Help transform massive volumes of documents, voice recordings, images, and video into actionable intelligence
Design and build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI to power next-generation enterprise capabilities

Requirements

Python (required) for AI/ML development
Java, with hands-on experience building backend services and enterprise integrations
Ability to work across both Python and Java codebases, integrating AI/ML components into Java-based enterprise systems
Proven experience building and operating production-grade AI/ML systems
Strong understanding of data pipelines and distributed data processing
Hands-on experience in one or more of the following areas: Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Vector Search & Embeddings, Multimodal AI, AI Agents/Agent Frameworks, Prompt Engineering, Semantic Models
Experience working in large-scale enterprise data environments, including Architecture, Data lakes, and lakehouse architectures, Streaming Kafka, and event-driven architectures
Experience with MLOps workflows
Experience with observability tools such as Datadog and AWS CloudWatch

Benefits

Work on petabyte-scale unstructured data challenges
Build with the latest GenAI and Agentic AI technologies
Transform unstructured data into enterprise intelligence
Join a team shaping the future of AI-powered decision making

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonJavaAI/ML developmentdata pipelinesdistributed data processingLarge Language Models (LLMs)Retrieval Augmented Generation (RAG)Vector SearchMLOps workflowsprompt engineering