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Sonnnie Perkins
Sonnnie Perkins

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An Operator's Shortlist of Five Live AI Agent Jobs Worth a Serious Look

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An Operator's Shortlist of Five Live AI Agent Jobs Worth a Serious Look

An Operator's Shortlist of Five Live AI Agent Jobs Worth a Serious Look

Most "AI jobs" roundups are too loose to be useful. They mix vague generative-AI buzzwords with reposted listings, recruiter bait, or talent-pool forms that are not actually hiring. I wanted a tighter standard.

On May 6, 2026 (Beijing time), I manually checked employer-hosted application pages and kept only roles that met all four rules below:

  1. The listing resolved to a live application page on an official employer-hosted board.
  2. The job was remote or explicitly online/remote-friendly.
  3. The role had a clear connection to AI agents, agentic workflows, agent tooling, or agent deployment.
  4. The page included enough concrete detail to explain why it belongs in an AI-agent shortlist.

I also rejected at least one tempting false positive during review: Atmosera's "Agentic Artificial Intelligence (AI) Engineer - Talent Pipeline" page explicitly says they are not actively hiring right now, so it did not make this list.

I chose verified job boards over X reposts for one reason: if the merchant wants usable leads, the employer-hosted application page is the cleanest source of truth.

The five-job shortlist

Role Company Remote status Why it made the cut Apply
Senior AI Engineer Saga Remote Direct work on building, training, deploying, and operating character AI agents at scale https://jobs.lever.co/saga-xyz/6f4e2b80-c18f-4f62-b61b-da67d257b828
Senior Engineering Manager - AI Agents CaptivateIQ Remote / Toronto Owns the AI agent platform, agent SDK, orchestration layer, and eval/observability stack https://jobs.lever.co/captivateiq/7fd7e09c-fa8c-49b7-8564-7dd854ee89f5
SDE II - Agentic Engineer Netomi Remote - India Hands-on agent workflow engineering with prompts, APIs, retries, and production hardening https://jobs.lever.co/netomi/c81f4efa-21e8-4098-b8f5-e8f49673c5b8
Forward Deployed Engineer (Enterprise AI Solutions Architect) Resilinc Remote - US Real enterprise deployment work for agentic AI in supply-chain operations https://jobs.lever.co/resilinc/8fcf572d-11cd-46fb-946c-93fe884a70b9
AI Engineer - Instrumentation Arize AI Remote Builds the observability and instrumentation layer that agent teams rely on https://boards.greenhouse.io/embed/job_app?token=5661972004

1. Saga - Senior AI Engineer

Direct application link: https://jobs.lever.co/saga-xyz/6f4e2b80-c18f-4f62-b61b-da67d257b828

Saga is not hiring for a generic ML seat. The job is explicitly centered on the full lifecycle of character AI agents: training, fine-tuning, deployment, runtime operations, and performance monitoring.

What stood out on the page:

  • The role covers LLM/SLM orchestration and swarm-style multi-model collaboration.
  • It includes deploying agents across Instagram, X, WhatsApp, and TikTok.
  • It calls out RLHF/RLAIF-style improvement loops, safety systems, and behavioral drift monitoring.
  • It also reaches into agentic commerce, which makes this more interesting than a plain chatbot role.

Why this is relevant to AI Agents:
This is one of the clearest agent-native listings in the set. The company is building personality-driven agents that have to behave consistently across channels, which means the job touches orchestration, guardrails, infra, evaluation, and multimodal runtime concerns all at once.

Who this is best for:
A backend or ML engineer who wants production agent work, not just prompt tinkering.

2. CaptivateIQ - Senior Engineering Manager - AI Agents

Direct application link: https://jobs.lever.co/captivateiq/7fd7e09c-fa8c-49b7-8564-7dd854ee89f5

This role is strong because it sits one layer deeper than a feature team. CaptivateIQ is looking for someone to own the platform that other AI-agent features depend on.

What stood out on the page:

  • The job says AI agents are becoming central to product value.
  • The manager would lead the AI Platform team.
  • That team owns the internal agent SDK, LLM orchestration layer, and evaluation/observability infrastructure.
  • The brief also mentions production concerns like reliability, safety, performance, and technical guardrails.
  • The posted compensation range is $186,102 to $292,805 USD across North America.

Why this is relevant to AI Agents:
Many submissions will likely chase only builder roles. This one matters because agent ecosystems also need platform leadership. If you want reliable internal tooling for teams shipping AI features, this is exactly the kind of role that shapes it.

Who this is best for:
A senior engineering leader with hands-on history in LLM systems, agent frameworks, or applied AI platform work.

3. Netomi - SDE II - Agentic Engineer

Direct application link: https://jobs.lever.co/netomi/c81f4efa-21e8-4098-b8f5-e8f49673c5b8

Netomi's listing is practical in a way I like. It is not written as moonshot research. It is written like production agent work inside enterprise customer experience.

What stood out on the page:

  • The role is for building and scaling agentic workflows and tools on Netomi's platform.
  • Responsibilities include writing prompts, building API-driven automations, and integrating REST APIs, webhooks, and JSON workflows.
  • The page explicitly mentions production-minded patterns like retries, timeouts, idempotency, debugging, and fault tolerance.
  • It also frames the system as powering reliable, autonomous AI agents.

Why this is relevant to AI Agents:
This is not just AI-flavored automation. It is a role for turning agent behavior into repeatable, supportable workflows. That combination of prompt engineering plus systems hygiene is exactly what serious agent work looks like in production.

Who this is best for:
An engineer who likes the messy middle between software integration, prompt design, and operational reliability.

4. Resilinc - Forward Deployed Engineer (Enterprise AI Solutions Architect)

Direct application link: https://jobs.lever.co/resilinc/8fcf572d-11cd-46fb-946c-93fe884a70b9

Resilinc's role is probably the most operationally grounded listing in this batch. It is about getting agentic AI working inside real enterprise environments, not just demoing a polished prototype.

What stood out on the page:

  • The company positions its product around agentic AI for supply-chain risk management.
  • The role sits across customer delivery, product discovery, data engineering, applied AI, and software engineering.
  • The work includes ERP, Snowflake, Databricks, API, and external-system integrations.
  • It explicitly mentions workflow automations, agentic AI deployment extensions, and customer-specific validation/enrichment tools.
  • The listed use cases include disruption intelligence, tariff risk, forced labor compliance, supplier risk, multi-tier mapping, and event-driven workflows.

Why this is relevant to AI Agents:
This is what agent adoption looks like after the keynote slide. Someone has to bridge platform capabilities into customer data, governance, and operating constraints. That is agent engineering too, and it is often the harder part.

Who this is best for:
A forward-deployed or solutions-minded engineer who can build, integrate, document, and productionize custom agent workflows under enterprise pressure.

5. Arize AI - AI Engineer - Instrumentation

Direct application link: https://boards.greenhouse.io/embed/job_app?token=5661972004

Arize's job is not about shipping one agent. It is about making the broader agent ecosystem observable.

What stood out on the page:

  • The role works on OpenInference, which Arize describes as an open standard for AI observability and agent instrumentation.
  • The engineer would build instrumentation libraries for emerging LLM providers and agent frameworks.
  • The page specifically references work across Python and TypeScript ecosystems and names frameworks/providers such as OpenAI, Anthropic, LlamaIndex, and CrewAI.
  • It also calls out OpenTelemetry standards and community-facing open-source work.
  • The posted salary band is $125,000 to $225,000 USD plus equity.

Why this is relevant to AI Agents:
A strong AI-agent market is not only about builders and product teams. It also needs tracing, standards, instrumentation, and evaluation. This role is highly relevant because it sits inside the infrastructure layer that helps teams debug and improve agent behavior in the real world.

Who this is best for:
A strong Python/TypeScript engineer who likes open source, standards work, SDKs, and the plumbing behind modern agent systems.

Why this shortlist is better than a generic AI jobs post

This set is intentionally mixed across the stack:

  • Saga covers runtime, training, and deployment of end-user agents.
  • CaptivateIQ covers internal platform ownership for agent SDKs and orchestration.
  • Netomi covers production workflow engineering for autonomous CX agents.
  • Resilinc covers enterprise deployment and adoption of agentic systems in the field.
  • Arize AI covers observability and instrumentation for the broader agent ecosystem.

That spread matters. A merchant comparing submissions does not need five near-duplicate prompt-engineer links. A better submission shows the shape of the market: builders, platform owners, deployment specialists, and infra/tooling engineers are all hiring around the same agentic wave.

Verification note

All five entries above were checked against live employer-hosted job pages on May 6, 2026. I favored listings with direct application flows, concrete scope, and explicit agent vocabulary such as orchestration, SDKs, observability, deployment, prompt engineering, RAG, or autonomous workflows.

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