VECTOR DISTRIBUTION
VECTOR DISTRIBUTION

60 Vector Jobs Hiring in Georgia

Design and maintain RAG workflows: document chunking, embeddings, vector indexing, retrieval ... for distributed systems. 2+ years of Experience with evaluating and mitigating retrieval ...

... Build vector database integrations (pgvector, Oracle AI Vector Search) for semantic search ... , and globally distributed teams on AI-enhanced database solutions Define engineering best ...

Vector databases such as Pinecone, Weaviate, FAISS, or ChromaDB. RAG architectures and semantic search. REST APIs, distributed systems, and scalable backend design. Experience with cloud platforms:

Platform Engineering Lead

Atlanta, GA · On-site

$98K - $129K/yr

Deep architectureexpertise:event-driven architectures, API-first patterns,distributed-systemsreliability, and modern data platforms (SQL / NoSQL; vector search exposure preferred). Strong DevOps & ...

New

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... vector databases, LLM integration, and agentic frameworks like LangChain, LangGraph * Natural analytical mindset with demonstrated ability to explore data, debug complex distributed systems, and ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... vector databases, LLM integration, and agentic frameworks like LangChain, LangGraph * Natural analytical mindset with demonstrated ability to explore data, debug complex distributed systems, and ...

Sr Data Engineer

Atlanta, GA

$110K - $132K/yr

... vector databases, LLM integration, and agentic frameworks like LangChain, LangGraph * Natural analytical mindset with demonstrated ability to explore data, debug complex distributed systems, and ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... vector databases, LLM integration, and agentic frameworks like LangChain, LangGraph * Natural analytical mindset with demonstrated ability to explore data, debug complex distributed systems, and ...

DevOps Platform Engineer

Duluth, GA · On-site

$48.50 - $66.50/hr

Provision and manage the agentic AI platform infrastructure - LLM API gateway, vector database ... Experience with remote device management for distributed hardware fleets Note: All offers are ...

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Contractor

Re-posted yesterday


Job description


AI Engineer
work onsite in Scottsdale AZ
AI Engineer.
About the Role
We are seeking an experienced AIML Engineer to design, build, and operate AI/ML infrastructure and agentic systems. This role involves developing MCP servers and agents, integrating LLMs, and implementing RAG pipelines for production environments.
Key Responsibilities
Design, build and operate MCP servers and MCP agents that host, orchestrate and monitor AI/agent workloads.
Develop agentic AI, prompt engineering patterns, LLM integrations and developer tooling for production use.
Own deployment, scaling, reliability and cost-efficiency on Kubernetes/Docker and Google Cloud with automated CI/CD
Design and implement RAG (RetrievalAugmented Generation) pipelines and integrations with vector stores and retrieval tooling; use LangChain and Langfuse for orchestration, chaining, and observability.
Core Responsibilities
Implement and maintain MCP server and agent code, APIs, and SDKs for model access and agent orchestration.
Design agent behavior, workflows and safety guards for agentic AI systems.
Create, test and iterate prompt templates, evaluation harnesses and grounding/chainofthought strategies.
Integrate LLMs and model providers (selfhosted and cloud APIs) with unified adapters and telemetry.
Build developer tooling: CLI, local runner, simulators, and debugging tools for agents and prompts.
Containerize services (Docker), manage orchestration (Kubernetes/GKE), and optimize nodes, autoscaling and resource requests.
Ensure observability: logging, metrics, traces, dashboards, alerting and SLOs for model infra and agents.
Create runbooks, playbooks and incident response procedures; reduce MTTR and perform postmortems.
Design and maintain RAG workflows: document chunking, embeddings, vector indexing, retrieval strategies, reranking and context injection.
Integrate and instrument LangChain for composable chains, agents and tooling; use Langfuse (or equivalent tracing) to capture prompts, model calls, RAG traces and evaluation telemetry.
Required Skills & Experience
5+ years of Strong Software Engineering (Python/NodeJS), system design and production service experience.
2+ years of Experience with LLMs, prompt engineering, and agent frameworks.
2+ years of Experience Practical experience implementing RAG: embeddings, vector DBs and retrieval tuning.
2+ years of Experience with LangChain patterns and with toolchain telemetry (Langfuse or similar) for prompt/model traceability.
5+ years of Experience with Kubernetes, Docker, CI/CD and infrastructureascode experience.
2+ years of Experience with Practical experience with Google Cloud Platform services
2+ years of Experience with Observability, testing, and security best practices for distributed systems.
2+ years of Experience with evaluating and mitigating retrieval/augmentation failures, hallucinations, and leakage risks in RAG systems.
Familiarity with vendor and opensource vector stores and embedding providers.
Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or ArgoCD)