Senior AI Platform Engineer - Production Agents & Pipelines

Collaboration.Ai; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Collaboration.Ai in Minnesota is seeking an experienced software engineer to build the agentic systems and data pipelines behind NetworkOS’s AI capabilities: production agent workflows built on industry-leading agent SDKs and harnesses, MCP servers, and Agent Skills standards; the eval and observability layer that keeps LLM quality measurable; and the ingestion pipelines that turn messy, diverse data sources into queryable knowledge.

This is an execution seat, not an ivory tower.

Qualifications

• 7+ years of professional software engineering experience, with 3+ years focused on AI/ML or data engineering.
• Production agentic/LLM application experience — built and operated systems around LLM APIs serving real users: agents, tool-use, or orchestrated LLM workflows
• Data engineering background — robust, scalable pipelines for AI/ML workloads.
• LLM operations experience — evals and observability for production LLM systems (quality, cost, latency).
• Production retrieval experience — vector databases and/or search engines (OpenSearch, Elasticsearch).
• Modern Python stack proficiency — FastAPI, Pydantic, async/await, modern dependency management.
• AI-native workflows — demonstrated ability to leverage Claude Code/Codex or similar agentic coding tools to accelerate development.
• Experience with Docker, Kubernetes, and AWS.
• US citizenship required (DoD contracting — IL4/IL5 environments — and FedRAMP compliance)

Responsibilities

• Ship production agent systems — design, build, and operate agentic workflows powering AI-driven matching, analysis, and data intelligence.
• Operationalize LLM quality — build the eval and observability layer with Langfuse and related patterns for measurable quality and latency.
• Engineer data pipelines — robust ingestion of documents and external sources into knowledge bases.
• Own retrieval quality — hybrid search with vector/keyword retrieval and continuous improvement.
• Accelerate with AI — build custom MCP tools and Agent Skills to speed up development.
• Execute alongside the team — pair with full-stack engineers on AI integration and incident response.

Skills

AI/ML engineering

Data pipelines

LLM workflows

Production systems

Retrieval systems

Python

Cloud (AWS)

Tools

Docker

Kubernetes

AWS

FastAPI

Pydantic

OpenSearch

Kafka/Kinesis

Job description

Collaboration.Ai in Minnesota is seeking an experienced software engineer to build the agentic systems and data pipelines behind NetworkOS’s AI capabilities: production agent workflows built on industry-leading agent SDKs and harnesses, MCP servers, and Agent Skills standards; the eval and observability layer that keeps LLM quality measurable; and the ingestion pipelines that turn messy, diverse data sources into queryable knowledge.

This is an execution seat, not an ivory tower.