Opportunity

Senior AI Engineer - Agentic AI & LLM Production Systems in Columbus

Location Columbus
Company Toptal
Source weworkremotely
Posted 2026-10-22 18:54:42

Career & Market Insight

This role sits at the cutting edge of AI engineering — specifically agentic systems, which are among the fastest-growing and most in-demand specializations in the industry as of 2024–2025. Experience shipping multi-agent workflows and production-grade LLM systems to enterprise clients is a rare, highly marketable skill set.

Compensation context: No salary is listed, which is a mild yellow flag for transparency. However, Toptal and similar talent platforms typically offer contractor or project-based engagements. Market rates for senior AI Engineers with agentic system expertise range from $150K–$220K/year (or $100–$180/hr on contract), depending on seniority and engagement type.

Skills developed in this role are in extremely high demand:

  • Multi-agent orchestration (LangGraph, AutoGen, Claude/OpenAI Agent SDKs)
  • Model Context Protocol (MCP) — a rapidly emerging standard
  • GCP infrastructure (GKE, Cloud Run, Pub/Sub, BigQuery)
  • Production AI safety, guardrails, and latency optimization

Green flags: "Move beyond proof-of-concept" signals real enterprise impact; "high execution agency" suggests a senior IC role with meaningful ownership; frontier model exposure is a strong resume builder.

Potential red flags: No salary transparency; the Toptal model typically means contractor/freelance rather than full-time employment with benefits. Candidates should clarify engagement type, duration, and benefits eligibility before applying.

Headquarters: (Remote — US Only)

We are seeking a highly hands-on AI Engineer with a proven track record of shipping agentic AI systems into production for enterprise environments. In this role, you will design, build, and deploy production-grade AI agents capable of multi-agent orchestration, complex tool execution, and dynamic context management. You will implement robust safety guardrails and integrate frontier models using leading agent frameworks and cloud infrastructure.

This position is remote within the US (East Coast time zone slightly preferred) with minimal travel required.

Tasks and Deliverables

  • Design and deploy autonomous and multi-agent orchestration workflows capable of executing complex, multi-step enterprise processes.
  • Implement structured tool-use frameworks and integrate external APIs and services using protocols such as Model Context Protocol (MCP).
  • Engineer advanced prompt strategies, dynamic context management, and memory layers to optimize model performance and reasoning accuracy.
  • Implement production-grade guardrails, schema enforcement, latency optimization, and defensive exception handling across all agentic workflows.
  • Deploy, scale, and maintain agentic microservices on cloud infrastructure using modern containerized and serverless platforms.

Required Experience

  • Production Agent Experience: Demonstrated, hands-on software engineering experience building, testing, and shipping autonomous agent systems and tool-calling workflows into production environments.
  • Framework & Model SDK Expertise: Strong proficiency in at least one major model ecosystem: Anthropic (Claude Agent SDK, Model Context Protocol), OpenAI (OpenAI Agents SDK, Responses API, File Search), or GCP Vertex AI (Gemini, Google ADK / Vertex AI Agent Engine).
  • Cloud Infrastructure (GCP): Experience building and deploying distributed applications on Google Cloud Platform, using services such as GKE, Cloud Run, Pub/Sub, and BigQuery.
  • Core Software Engineering: Strong foundation in software design patterns, API integrations, structured outputs (Pydantic/JSON schemas), and microservices architecture.
  • Location: Based in the US (East Coast time zone slightly preferred).

Engagement Highlights

  • Enterprise Production Scale: Move beyond proof-of-concept builds to deploy actual, living agent systems that automate mission-critical enterprise processes.
  • Frontier Tech Stack: Work directly with state-of-the-art agent SDKs, Model Context Protocol, and multi-model ecosystems across Anthropic, OpenAI, and GCP.
  • Remote Autonomy: Enjoy a fully remote US-based role with high execution agency and low friction.

To apply: https://weworkremotely.com/remote-jobs/toptal-ai-engineer-agentic-systems

Frequently Asked Questions

Is this AI Engineer role fully remote?
Yes, this position is fully remote, but it is restricted to candidates based in the United States. A slight preference is given to candidates in the East Coast timezone.
What AI frameworks and SDKs are required for this role?
Candidates need strong proficiency in at least one major model ecosystem: Anthropic (Claude Agent SDK, MCP), OpenAI (Agents SDK, Responses API), or GCP Vertex AI (Gemini, Google ADK). Production experience shipping agent systems is mandatory.
What cloud platform experience is needed?
Experience with Google Cloud Platform is required, specifically with services such as GKE, Cloud Run, Pub/Sub, and BigQuery for deploying distributed agentic microservices.
Is this a full-time employee role or a contract/freelance engagement?
The posting does not explicitly clarify the engagement type, but given that it is listed via Toptal — a talent marketplace — this is likely a contract or project-based engagement. Candidates should confirm this before applying.
What level of experience is expected for this AI Engineer position?
This is a senior-level, hands-on role requiring a demonstrated track record of shipping autonomous agent systems to production enterprise environments — proof-of-concept experience alone is not sufficient.
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