AI Engineer

Data Inc
Los Angeles, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Los Angeles, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Automated Storage and Retrieval Systems
Cloud Engineering
Encodings
Continuous Integration
Information Engineering
Data Infrastructure
Amazon DynamoDB
Graph Database
Python
Knowledge Management
Machine Learning
Redis
Azure
Search Technologies
Amazon Web Services (AWS)
Large Language Models
Prompt Engineering
Spark
Model Validation
Generative AI
Backend
Containerization
AI Platforms
Kubernetes
Deployment Automation
Data Management
Machine Learning Operations
Virtual Agents
Data Pipelines
Automation Anywhere
Docker
Databricks
Microservices

Job description

Seeking a Senior AI Engineer with strong expertise in Generative AI, AWS cloud services, and data platform engineering to build and scale production-grade AI solutions. The role focuses on LLM-powered applications, RAG architectures, vector search, knowledge graphs, data pipelines, and agentic AI systems. The candidate will drive end-to-end AI platform development, deployment, and operational excellence.

Roles & Responsibilities

  • Design and implement Generative AI solutions using LLMs, RAG, embeddings, and prompt orchestration.
  • Build vector search and retrieval systems using OpenSearch and knowledge graph solutions using Neptune.
  • Develop agent-based AI workflows using LangGraph, AutoGen, CrewAI, or similar frameworks.
  • Design and maintain scalable data pipelines, embedding pipelines, and knowledge management systems using Databricks and Spark.
  • Develop secure, scalable backend APIs and microservices to expose AI capabilities.
  • Build and manage CI/CD pipelines, containerized deployments, and production AI environments.
  • Implement AI observability, model evaluation, monitoring, security, and governance best practices.
  • Collaborate with product and engineering teams to deliver enterprise-grade AI solutions.

Requirements

  • Generative AI / LLM Development (RAG, Embeddings, Prompt Engineering)
  • AWS Cloud Services (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis)
  • Vector Search & Retrieval Systems
  • Graph Databases & Knowledge Graphs
  • LangChain and LlamaIndex
  • Agentic AI Frameworks (LangGraph, AutoGen, CrewAI)
  • Databricks & Apache Spark
  • Python Development, APIs, and Microservices
  • CI/CD, Docker, Kubernetes, and MLOps
  • AI Observability, Evaluation, Security, and Governance

Experience

  • Strong experience building production-grade Generative AI and data platforms.
  • Hands-on expertise in LLM applications, retrieval systems, and knowledge engineering.
  • Experience with cloud-native architectures and enterprise AI deployments.
  • Background in AI/ML Platform Engineering, Data Engineering, or Generative AI solutions.

Preferred Qualifications

  • AWS Certifications (Solutions Architect, Machine Learning Specialty, or Data Engineer).
  • Experience with LLM evaluation frameworks, AI governance, and MCP-style architectures.
  • Familiarity with advanced MLOps and agent-based AI architectures.

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