An AI agent developer builds systems that decide and act - planning, tool calls, and multi-step execution. A RAG engineer builds systems that retrieve and ground answers in your documents. F5 Hiring Solutions places agent developers at $600-$1,150 per week and RAG engineers at $600-$1,050 per week, both inside its $375-$1,200 per week, all-inclusive range, shortlisted in 7-14 business days.

These two roles get conflated in job postings constantly, and the cost of getting it wrong is a quarter of engineering time spent building the wrong layer. Both work with language models. Both write Python. Both care about evaluation. The similarity ends there.

The distinction is architectural. A retrieval system answers a question by finding the right context. An agent system accomplishes a task by choosing a sequence of actions. Those are different problems with different failure modes, and the engineers who are good at one are not automatically good at the other.

What Does an AI Agent Developer Actually Build?

An AI agent developer builds the control loop: the code that decides what the model should do next, calls external tools, handles the results, and knows when to stop. The deliverable is a system that completes multi-step tasks reliably, not one that produces good text.

That means tool and function definitions the model can call correctly. It means state management across a run, so step four knows what happened in step two. It means retry logic, timeout handling, and a hard ceiling on iterations so a confused agent cannot loop forever burning tokens.

The hard part of agent work is failure handling, not the happy path. A demo agent that books a meeting works on the first try in a controlled test. A production agent has to survive an API returning a 500, a tool returning a malformed payload, and a model choosing a nonsensical action.

Agent developers also own the cost profile. Every planning step is another model call, so an agent that takes twelve steps where four would do is a budget problem as much as a latency problem.

What Does a RAG Engineer Actually Build?

A RAG engineer builds the retrieval layer: document ingestion, chunking, embedding, vector storage, retrieval scoring, reranking, and context assembly. The deliverable is grounded, accurate output against a specific corpus.

The hard part is that retrieval quality is corpus-specific. A chunking strategy that works for support articles fails on legal contracts, where meaning spans pages and a mid-clause split destroys it. Embedding model choice, chunk size, and overlap are tuned against the actual documents, not chosen from a default.

RAG engineers own evaluation as a core deliverable, not a QA afterthought. Faithfulness, context precision, and answer relevancy get measured continuously, ideally wired into CI so a retrieval regression fails the build.

If your users are asking questions your documents already answer, this is the role you need.

How Do the Two Roles Compare Side by Side?

The table below separates the roles on the dimensions that actually change your hiring decision. Both sit inside F5's range of $375-$1,200 per week, all-inclusive.

AI agent developer versus RAG engineer: scope, skills, failure modes, and cost through F5
Dimension AI Agent Developer RAG Engineer
Core deliverable A control loop that completes multi-step tasks A retrieval pipeline that grounds answers in your documents
Primary skills Tool and function calling, planning loops, state management, retry and fallback design Chunking strategy, embedding selection, hybrid retrieval, reranking, vector database operations
Typical failure mode Runaway loops, silent tool failures, unbounded token spend Confidently wrong answers from retrieved context that looked relevant but was not
How you measure success Task completion rate, steps per task, cost per completed task Faithfulness, context precision, answer relevancy
Hire first when The work spans systems and requires actions, not just answers Users are asking questions your existing documents already answer
F5 weekly rate, all-inclusive $600-$1,150 per week $600-$1,050 per week
Who should NOT use F5 Teams that need a two-week prototype and nothing afterwards, teams that want to browse candidate profiles without a discovery call, and teams that require the engineer on their own payroll for equity or IP-structure reasons. F5 places full-time professionals through a concierge process, so short scoped work belongs on a freelance marketplace instead.

Which Role Should You Hire First?

Hire the RAG engineer first if your problem is answers. Support deflection, internal knowledge search, and document question-answering are retrieval problems, and retrieval is the cheaper and better-understood layer to build.

Hire the agent developer first if your problem is actions. Anything that updates records, triggers workflows, or coordinates across several systems needs a control layer, and no amount of retrieval quality substitutes for it.

Most teams that eventually need both end up building retrieval first anyway, because agents that act on your data need a reliable way to read it. Retrieval becomes a tool the agent calls.

What Should You Ask in the Interview?

For an agent developer, ask what happens when a tool call fails twice in a row. A candidate who has shipped production agents describes retry ceilings, fallback paths, and a hard iteration stop. A candidate who has only built demos describes the happy path.

For a RAG engineer, ask how they chose their chunk size on the last system they built. A real answer references the document structure and the evaluation numbers that followed. A weak answer names a number with no reasoning behind it.

For both, ask what they measured. Engineers who have run these systems in production have opinions about evaluation because they have been burned by shipping something that demoed well and failed on real traffic.

What Do These Roles Cost?

F5 Hiring Solutions places AI agent developers at $600-$1,150 per week and RAG engineers at $600-$1,050 per week, both all-inclusive within F5's full range of $375-$1,200 per week, all-inclusive. That covers salary, HR, compliance, equipment, and management, with no setup, recruiting, or termination fees.

The US benchmark is imprecise by necessity. BLS publishes no occupation code for either role, so the closest standard occupation is Software Developers (SOC 15-1252), with a May 2025 OEWS median of $135,980. Applying the BLS ECEC multiplier of 1.4265 puts the fully loaded median near $193,975.

That figure is a benchmark for software engineering labour, not a measured AI-role wage. Treat it as a floor for comparison rather than a precise market rate.

F5 draws from 85,500+ candidates in its internal sourcing and screening database, serves 250+ companies, and reports a 95% client retention rate, measured as clients who continue beyond the first 3 months.

The Bottom Line

Retrieval and control are different layers of the same stack. A RAG engineer makes your system's answers trustworthy. An agent developer makes your system's actions reliable. Hiring one and expecting the other is the most common and most expensive mistake in AI staffing right now.

Decide which layer is blocking you, hire for that specialism, and add the second when the first is stable. F5 delivers a shortlist for either role in 7-14 business days, with a zero-cost replacement within 7-14 days if the fit is wrong.

To scope which role your build actually needs, schedule a call with Joel Deutsch.

Frequently Asked Questions

What is the core difference between an AI agent developer and a RAG engineer?

A RAG engineer builds the retrieval layer that grounds model output in your documents. An AI agent developer builds the control layer that decides what to do next and calls tools to do it. Retrieval answers questions; agents take actions. Most production systems eventually need both.

Which role should I hire first?

Hire the RAG engineer first if your users are asking questions your documents already answer. Hire the agent developer first if the work involves multi-step tasks across systems, like updating records or triggering workflows. Retrieval is usually the earlier and cheaper problem to solve.

Can one engineer cover both agent and RAG work?

Sometimes, at senior level. The skills overlap in evaluation and prompt design but diverge sharply in the hard parts: chunking and embedding strategy versus planning loops and tool-call reliability. F5 screens for the primary specialism first, then confirms secondary depth during technical review.

What does each role cost through F5?

F5 places AI agent developers at $600-$1,150 per week and RAG engineers at $600-$1,050 per week, both all-inclusive and inside F5's full range of $375-$1,200 per week, all-inclusive. That covers salary, HR, compliance, equipment, and management, with no recruiting or termination fees.

How do you tell a real agent developer from a framework tourist?

Ask what their agent does when a tool call fails twice in a row. A candidate who has shipped production agents will describe retry limits, fallback paths, and a hard stop on runaway loops. A candidate who has only built demos will describe the happy path and nothing else.

What US salary benchmark applies to these roles?

BLS publishes no distinct occupation code for AI agent or RAG engineering. The closest standard occupation is Software Developers, SOC 15-1252, with a May 2025 OEWS median of $135,980, roughly $193,975 fully loaded at the ECEC 1.4265 multiplier. Treat it as a benchmark, not a role-specific wage.

Do F5 engineers in these roles work exclusively for one client?

Yes. Every F5 professional is employed by F5 and assigned to a single client full-time, working your hours and inside your tooling. F5 is a managed remote workforce company, so the engineer is not shared across accounts or rotated between projects.

How fast can F5 deliver candidates for either role?

F5 delivers a shortlist within 7-14 business days for both roles. If the placed engineer is not the right fit, F5 sources a replacement within 7-14 days at zero cost, with no minimum engagement period and no termination fee.