Five Remote AI-Agent Roles That Already Expect You to Ship Agents
Five Remote AI-Agent Roles That Already Expect You to Ship Agents
Most AI job roundups are too loose with the label. A role mentions LLMs once, and suddenly it gets filed under AI agents.
I wanted a tighter bar.
For this shortlist, I only kept roles that were still open on May 6, 2026 on official company-hosted job pages and where the work itself is clearly agentic: building agents, orchestrating them, giving them tools, governing their behavior, or deploying them into real workflows.
I also avoided repost farms and vague generic AI titles. Every role below links straight to a live company application page.
How I filtered the list
- Official company-hosted application page only
- Remote or remote-friendly online role
- Live application form available on May 6, 2026
- Clear AI-agent relevance in the actual responsibilities, not just marketing copy
- No talent-pipeline placeholders and no generic AI jobs without agentic scope
1. Pioneer Talent Program: AI Application Engineer at Binance
Location: Remote, Asia
Type: Full-time / Pioneer Talent Program
Apply: https://jobs.lever.co/binance/2ef11b02-daff-4f10-819e-cb005ff1befd/apply
What the job is
This is an early-career engineering role, but it is not lightweight. The role is centered on building production AI agent workflows and internal AI systems that solve business problems rather than research demos.
Why it made the cut
The responsibilities are unusually explicit for an agent role. Binance is asking for someone who can:
- build AI agent workflows for real operational use cases
- integrate tools, APIs, internal services, databases, and knowledge sources into agent behavior
- improve quality, latency, reliability, safety, and cost
- work on prompt structures, orchestration logic, memory or retrieval patterns, and human handoff flows
That combination matters. It means the company is not hiring for prompt tinkering alone; it is hiring for production agent design with tool use, guardrails, and iterative evaluation.
Best fit
A strong fit for someone with internship or junior-level engineering experience who already thinks in terms of agent loops, tool calling, retrieval, and pragmatic shipping.
2. Sr. Software Engineer (Agentic Access) at Immuta
Location: Remote USA
Type: Full-time
Apply: https://jobs.lever.co/immuta/47767e99-640f-4662-be9b-79e70ae7a146/apply
What the job is
Immuta is hiring a senior backend engineer to work on what might be the least flashy and most important layer of the agent stack: governed data access for autonomous systems.
Why it made the cut
This role sits at the intersection of AI and enterprise data security. The brief is not generic AI infrastructure. It is specifically about the systems that allow autonomous agents to discover, authenticate against, and securely access governed enterprise data.
That is real agent work because production agents are only as useful as the systems they are allowed to touch. If you cannot solve governed access, policy enforcement, and reliable workflow execution, your agent platform does not survive enterprise deployment.
The role also points to concrete technical ownership:
- backend services and distributed workflows
- integrations with platforms such as Snowflake and Databricks
- TypeScript microservices, APIs, and Temporal workflows
- reliability and scale in Kubernetes environments
Best fit
Senior engineers who care less about demo magic and more about the hard plumbing that makes enterprise agents trustworthy.
3. Senior AI Engineer at Saga
Location: Remote
Type: Remote engineering role
Apply: https://jobs.lever.co/saga-xyz/6f4e2b80-c18f-4f62-b61b-da67d257b828/apply
What the job is
Saga is building character AI agents for studios, creators, and publishers. This role covers the full lifecycle: train, orchestrate, deploy, monitor, and improve agents that operate in public-facing environments.
Why it made the cut
This listing is one of the clearest examples of a role where the product is the agent. The engineer is expected to work on:
- LLM and SLM orchestration
- swarm-based architectures
- deployment of agents across platforms like Instagram, X, WhatsApp, and TikTok
- feedback loops such as fine-tuning, reward models, RLHF, and RLAIF
- behavior consistency, moderation, and drift monitoring
- multi-modal expansion into voice, video, and livestreaming
That is not adjacent to agent work. That is agent operations as the core product surface.
Best fit
Engineers with strong Python and systems instincts who want to work on public-facing autonomous behavior, especially where personality, moderation, and cross-platform deployment all matter at once.
4. Principal Agentic Engineer (Back-end) at Apply Digital
Location: Remote, Latin America
Type: Full-time permanent
Apply: https://jobs.lever.co/applydigital/10148a94-ebcb-40b7-a87a-10e45e864816/apply
What the job is
Apply Digital is hiring a senior technical lead to design and ship backend systems for AI-powered client products. This is a leadership role, but it is still hands-on and implementation-heavy.
Why it made the cut
This role stands out because it connects agentic engineering to client delivery, not just internal experimentation. The listing explicitly calls for someone who can:
- design distributed, cloud-native systems that integrate LLMs, vector databases, and AI agents
- lead technical direction across complex backend systems
- work directly with clients and internal teams to deliver production-grade solutions
- engineer teams of coding agents to accomplish implementation requirements
The application flow is also revealing: it asks candidates about production AI agents, RAG systems, vector databases, Google Cloud and Vertex AI, and agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or custom stacks.
That makes this role more than a backend lead opening with AI garnish. It is a serious agent systems role inside a delivery organization.
Best fit
Principal or staff-level backend engineers who can translate ambiguous client needs into robust agent-enabled systems and who are comfortable owning architecture in front of customers.
5. Agentic Solution Architect at Netomi
Location: Remote, Canada
Type: Full-time
Apply: https://jobs.lever.co/netomi/5efaed83-3786-467b-b492-1154e91e5af4/apply
What the job is
Netomi is hiring a customer-facing architect to design and deploy large-scale agentic AI systems for enterprise customer experience teams.
Why it made the cut
I included this role because a strong AI-agent market is not only hiring builders; it is also hiring translators who can turn messy business processes into autonomous workflows that actually run inside enterprises.
The role description is specific about that work:
- lead discovery with enterprise customers
- identify automation opportunities and design orchestration strategies
- create solution blueprints covering workflows, data exchanges, escalation logic, guardrails, analytics, and lifecycle design
- define agentic architectures across intents, actions, tools, integration points, and decision logic
- guide implementation, QA, workflow tuning, and governance
This is the kind of role that shows where the market is heading. Companies now need people who can connect agent design to operations, support stacks, APIs, security standards, and measurable delivery outcomes.
Best fit
Solutions architects, implementation leads, or product consultants who already know enterprise integrations and want to specialize in agent deployment rather than classic SaaS rollouts.
What these five roles say about the market
A useful pattern shows up when you line these jobs next to each other.
1. The market is moving past prompt-only roles
The strongest listings are asking for orchestration, tool integration, evaluation, latency, reliability, and guardrails. In other words, companies want systems people, not just prompt writers.
2. Agent work is splitting into distinct lanes
These five roles map cleanly to five lanes:
- core workflow builder: Binance
- governed enterprise access layer: Immuta
- public-facing agent product engineer: Saga
- client-delivery technical lead: Apply Digital
- enterprise deployment architect: Netomi
That matters for job seekers. Saying you want an AI agent job is too broad now. You need to know whether you want to build the runtime, the safety layer, the customer deployment motion, or the end-user product.
3. Real agent jobs are deeply integrated with other systems
Across the list, the recurring themes are APIs, retrieval, workflow engines, cloud deployment, decision logic, enterprise integrations, and human handoff. The interesting work is not isolated model use. It is connecting models to the rest of the stack responsibly.
Final shortlist
If I had to hand one concise set of live leads to someone targeting the AI-agent market on May 6, 2026, I would hand them these five:
- Binance — Pioneer Talent Program: AI Application Engineer https://jobs.lever.co/binance/2ef11b02-daff-4f10-819e-cb005ff1befd/apply
- Immuta — Sr. Software Engineer (Agentic Access) https://jobs.lever.co/immuta/47767e99-640f-4662-be9b-79e70ae7a146/apply
- Saga — Senior AI Engineer https://jobs.lever.co/saga-xyz/6f4e2b80-c18f-4f62-b61b-da67d257b828/apply
- Apply Digital — Principal Agentic Engineer (Back-end) https://jobs.lever.co/applydigital/10148a94-ebcb-40b7-a87a-10e45e864816/apply
- Netomi — Agentic Solution Architect https://jobs.lever.co/netomi/5efaed83-3786-467b-b492-1154e91e5af4/apply
That is a more useful snapshot than a bloated list of twenty weak matches. Each one is live, direct, and clearly tied to the real operating surface of AI agents.
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