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Senior AI Engineer

Flex Employee Services Irvine, CA

Irvine, CA

Today

$47 - $51/hr Full time Agentic Ai AI Ai Ml

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Job Description

Flex Employee Services seeks a Senior AI Engineer to architect, build, and operate a production-grade Generative AI and Data Platform on AWS, emphasizing LLM-powered capabilities, vector search, and graph-based knowledge systems, all within governed data pipelines. This onsite role in Irvine, CA offers the opportunity to shape scalable AI infrastructure across teams, with a compensation range of $47-$51 per hour and a requirement of five years of experience along with a Bachelor’s or Master’s degree.

Responsibilities

Operationalize LLM-enabled applications using retrieval augmented generation, embeddings, prompt orchestration, and evaluation pipelines.
Design and implement vector search solutions with Amazon OpenSearch.
Develop graph-based knowledge systems using Amazon Neptune.
Integrate Redis via ElastiCache and DynamoDB to support AI applications.
Build agentic workflows leveraging LangGraph, AutoGen, CrewAI, or equivalent frameworks.
Incorporate LangChain or LlamaIndex for retrieval orchestration, tool invocation, and context management.
Define standards for tool integration and context-sharing using MCP-style designs.
Evaluate LLM models and retrieval strategies based on latency, accuracy, cost, and context limits.
Design and scale data pipelines with Databricks and Apache Spark.
Develop data ingestion, transformation, document processing, embedding generation, and indexing pipelines.
Ensure data quality through validation, completeness, consistency, and monitoring.
Implement data governance, access controls, retention policies, auditability, and lineage tracking.
Develop secure and scalable backend services and APIs.
Define API standards, versioning, reliability, retry logic, circuit breakers, and idempotency practices.
Build reusable platform capabilities for multiple teams and applications.
Develop and manage CI/CD pipelines.
Deploy production systems using Docker and Kubernetes.
Implement blue/green deployments, canary releases, rollback strategies, and feature flags.
Monitor platform reliability, observability, security, data freshness, and cost optimization.
Define GenAI quality metrics covering grounding, retrieval relevance, response consistency, latency, and cost.
Implement prompt and version tracking, evaluation pipelines, and continuous improvement workflows.
Ensure AI security through access controls, authentication, data protection, responsible AI guardrails, privacy, and auditability.

Requirements

Generative AI / LLM capabilities including RAG, embeddings, and prompt engineering.
AWS Cloud expertise with OpenSearch, Neptune, DynamoDB, and ElastiCache/Redis.
Vector search and retrieval systems experience (OpenSearch or Vector DB).
Graph databases and knowledge graphs (Amazon Neptune).
LLM frameworks such as LangChain and LlamaIndex.
Agentic AI frameworks like LangGraph, AutoGen, or CrewAI.
Databricks and Apache Spark for data and embedding pipelines.
Backend/API development in Python with scalable APIs and microservices.
Proven experience delivering production-grade Generative AI solutions.
Strong Python programming skills and experience with distributed systems, API design, and scalable backend development.
Experience building end-to-end AI/ML platforms.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
Demonstrated track record of delivering production AI platforms and systems.
Solid background in end-to-end AI/ML lifecycle delivery.

Technologies

LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI
OpenSearch, Amazon Neptune, DynamoDB, ElastiCache (Redis)
Databricks, Apache Spark
Python
Docker, Kubernetes

Benefits

Dental insurance
Health insurance
Referral program
Vision insurance

Preferred Skills

Model evaluation frameworks and LLM observability tools
AI governance and compliance frameworks
Kubernetes and advanced MLOps practices
Model Context Protocol (MCP) patterns
Agent-based architectures

Domain Experience

AI/ML Platform Engineering
Generative AI / LLM Applications
Data Platform / Big Data Engineering

Soft Skills

Strong problem-solving and analytical thinking
Ability to communicate complex AI concepts clearly
Collaborative and cross-functional mindset
Ownership-driven and proactive execution

Application Questions

Are you comfortable working on W2? If not, please hold off on completing the application for now. We’ll be posting another opportunity in the future for 1099/C2C candidates.
Are you willing to work on a contract basis? If not, please hold off on completing the application for now. We’ll be posting another opportunity in the future for full time roles.
Do you have a minimum of 5 years of experience with Graph Databases (Amazon Neptune, Knowledge Graphs)?
Do you have a minimum of 5 years of experience with Agentic AI Frameworks (LangGraph / AutoGen / CrewAI)?
Do you have a minimum of 5 years of experience with Databricks & Apache Spark (data pipelines, embedding pipelines)?
Do you have a minimum of 5 years of experience with Backend/API Development (Python, scalable APIs, microservices)?
Do you have a minimum 5 years of experience with Generative AI / LLM (RAG, embeddings, prompt engineering)?
Do you have a minimum of 5 years of experience with AWS Cloud (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis)?
Do you have a minimum of 5 years of experience with Vector Search & Retrieval Systems (OpenSearch / Vector DB)?

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