Neptune Engineer Jobs

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1d ago

Senior AI Engineer

Flex Employee Services Irvine, CA

Irvine, CA

1d ago

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

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Job Description

The Senior AI Engineer role at Flex Employee Services focuses on designing, building, and scaling a production-grade Generative AI and Data Platform on AWS, with emphasis on LLM powered capabilities, vector search, graph-based knowledge systems, and governed data pipelines.

Responsibilities

Design and operationalize LLM powered applications using retrieval augmentation (RAG), embeddings, prompt orchestration, and evaluation frameworks.
Develop vector search solutions leveraging Amazon OpenSearch.
Build graph-based knowledge systems with Amazon Neptune.
Integrate AWS data stores such as ElastiCache (Redis) and DynamoDB to support AI workloads.
Construct agentic workflows using LangGraph, AutoGen, CrewAI, or equivalent frameworks.
Incorporate LangChain or LlamaIndex for retrieval orchestration, tool calling, and context management.
Define standards for tool integration and context sharing following MCP style designs.
Evaluate LLM models and retrieval strategies with a focus on latency, accuracy, cost, and context limits.
Design and build scalable data pipelines using Databricks and Apache Spark.
Develop data ingestion, transformation, document processing, embedding generation, and indexing pipelines.
Ensure data quality through validation, completeness, consistency, and ongoing monitoring.
Implement data governance, access controls, retention policies, auditability, and lineage tracking.
Develop secure and scalable backend services and APIs with robust design principles.
Define API standards, versioning, reliability, retry logic, circuit breakers, and idempotency.
Build reusable platform capabilities that serve multiple teams and applications.
Establish and manage CI/CD pipelines to support rapid development cycles.
Deploy production systems using Docker and Kubernetes, with blue/green, canary, rollback, and feature flag strategies.
Monitor platform reliability, observability, security, data freshness, and cost optimization.
Define and monitor GenAI quality metrics including 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

5+ years of experience in Generative AI and LLM work including RAG, embeddings, and prompt engineering.
Hands-on experience with AWS Cloud services such as OpenSearch, Neptune, DynamoDB, and ElastiCache/Redis.
Strong background in vector search and retrieval systems (OpenSearch or vector databases).
Proficiency with graph databases and knowledge graph concepts (Amazon Neptune).
Experience with LLM frameworks such as LangChain or LlamaIndex.
Experience with agentic AI frameworks like LangGraph, AutoGen, or CrewAI.
Experience building data pipelines with Databricks and Apache Spark (including embedding pipelines).
Backend/API development expertise in Python, including scalable APIs and microservices.
Proven track record of delivering production-grade Generative AI solutions.
Strong Python programming skills and familiarity with distributed systems, API design, and scalable backend development.
Experience building end-to-end AI/ML platforms and lifecycle delivery.
Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

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, or should you wait for a future 1099/C2C opportunity?
Are you willing to work on a contract basis, or should you wait for future full-time opportunities?
Do you have at least 5 years of experience with Graph Databases (Amazon Neptune, Knowledge Graphs)?
Do you have at least 5 years of experience with Agentic AI Frameworks (LangGraph / AutoGen / CrewAI)?
Do you have at least 5 years of experience with Databricks and Apache Spark (data pipelines, embedding pipelines)?
Do you have at least 5 years of experience with Backend/API Development (Python, scalable APIs, microservices)?
Do you have at least 5 years of experience with Generative AI / LLM (RAG, embeddings, prompt engineering)?
Do you have at least 5 years of experience with AWS Cloud (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis)?
Do you have at least 5 years of experience with Vector Search and Retrieval Systems (OpenSearch / Vector DB)?

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