Senior GenAI Engineer: Build Scalable AI Platform on AWS

Compunnel, Inc.; Los Angeles (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Compunnel, Inc. is seeking a Senior AI Engineer to design and build a production-grade Generative AI and Data Platform on AWS. This role will focus on enabling LLM-powered capabilities, integrating data pipelines, and operationalizing AI systems.

The ideal candidate will have strong experience in Generative AI, AWS ecosystem, and solid programming skills in Python. Responsibilities include building scalable applications, developing backend services, and ensuring system reliability through best practices in MLOps.

Qualifications

• Strong experience in Generative AI / LLM systems.
• Hands-on experience with the AWS ecosystem.
• Expertise in Amazon OpenSearch, DynamoDB, and Redis.
• Experience with LangChain / LlamaIndex frameworks.
• Strong programming skills, preferably in Python.
• Experience with Databricks and Apache Spark.
• Solid understanding of data pipelines and API design.
• Proven experience building production-grade AI platforms.

Responsibilities

• Build and operationalize LLM-powered applications.
• Design and implement scalable data pipelines.
• Develop backend services with secure APIs.
• Build and manage CI/CD pipelines for AI workflows.
• Implement secure AI systems with compliance measures.

Skills

Generative AI / LLM systems

AWS ecosystem

Amazon OpenSearch

Amazon Neptune

DynamoDB

Redis (ElastiCache)

LangChain

LlamaIndex

LangGraph

AutoGen

CrewAI

Python

Databricks

Apache Spark

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Docker

Kubernetes

Job description

Compunnel, Inc. is seeking a Senior AI Engineer to design and build a production-grade Generative AI and Data Platform on AWS. This role will focus on enabling LLM-powered capabilities, integrating data pipelines, and operationalizing AI systems.

The ideal candidate will have strong experience in Generative AI, AWS ecosystem, and solid programming skills in Python. Responsibilities include building scalable applications, developing backend services, and ensuring system reliability through best practices in MLOps.