What are the responsibilities and job description for the Senior AI Engineer position at Data Capital Inc?
Job Summary
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.
Required Skills
* 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.
Location & Work Model
* Irvine, CA & Los Angeles, CA
* Hybrid/Onsite: 4 days onsite per week (2–3 days in Irvine office, 1 day in Downtown LA office) with limited remote flexibility.