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What we place

Agentic AI Engineer Recruitment

Digitalent, the AI/ML executive search firm, places agentic AI engineers into VC-backed startups and established companies across the US, UK and Australia. Roles cover agent architecture, tool use, evaluation and the applied engineering that turns a working demo into something customers rely on.

Agentic AI at Digitalent

Agentic AI at Digitalent

500+

AI/ML placements since January 2021

200+

executive and leadership hires

90%+

still in post after 12 months

By market
300+ US, 100+ UK, 100+ Australia
By seniority
200+ executive and leadership hires, 300+ senior individual contributors
Brief to shortlist
approx. one week
Brief to offer
approx. three weeks for a permanent (full-time) hire, approx. one week for a contract hire

Figures updated August 2026.

Roles

What we place in Agentic AI

These roles come up most often, at both leadership and senior individual contributor level.

  • Heads of Agentic AI and Principal Agentic AI Leads
  • Agentic AI engineers with real depth in tool calling, multi-agent orchestration and state management
  • Forward deployed engineers who specialise in agentic AI
  • Applied engineers building on frontier models
  • Evaluation and reliability engineers
  • Inference and serving engineers
  • Post-training and fine-tuning specialists

The hard part

What makes these searches hard

Almost everyone claims this experience now and very little of it is production experience. The useful question is not whether somebody has built an agent, it is whether they have kept one working against real users, and whether they can describe how they knew it was working.

The depth we test for is specific. Has this person built tool calling, planning and execution loops, state and memory, human-in-the-loop controls? Do they think in retries, timeouts, checkpointing, idempotency and safe failure modes, or only in prompts? Enterprise agent platforms automate long-running, knowledge-intensive work, which means holding coherent state and knowledge across extended interactions, understanding organisational context, and sitting inside existing workflows and enterprise software. That is a different discipline from building something impressive in a notebook.

We screen on evaluation methodology before anything else, because it is the cleanest separator between people who have shipped and people who have prototyped. Task suites, regression tests, acceptance criteria, quality thresholds, rather than a feeling that the demo went well. It is also the thing a hiring manager most often forgets to ask about until the second round.

The most valuable people have owned a zero to one enterprise deployment end to end: discovery, prototype, production, rollout, then iterating until there is measurable return. That last part is rare. Plenty of engineers have shipped an agent. Far fewer have stayed with one long enough to prove it moved a number the business cares about.

Job titles have not settled either. The same role reaches us as Agent Engineer, Agentic AI Engineer, Applied AI Engineer or simply AI Engineer, and a growing share of the work now sits with forward deployed engineers who specialise in agentic systems. A search keyed on job title alone misses most of the market.

Case study

Placements in this area

Client names are withheld where the company is still in stealth.

A Principal Agentic AI Lead to set the AI strategy at FleetGuru.ai

FleetGuru.ai, a B2B software scale-up on the Gold Coast, hired a Principal Agentic AI Lead through Digitalent, brought in to set the enterprise AI strategy and design the core agentic framework.

This was a location problem before it was a skills problem. Elite AI engineers are scarce on the Gold Coast in a way they are not in Sydney or Melbourne, and the brief needed a PhD-level architect willing to commit to a scale-up rather than a lab or a major. It also had to be someone senior enough to define the enterprise AI strategy and design the core agentic framework rather than execute somebody else’s, and to do that to the standard set by an AI product leader who reads twenty research papers a month. People who can do that are rarely looking, and rarely looking outside a capital city.

A marathon search rather than a fast one. The hire set the enterprise AI strategy, designed the core agentic framework and built the foundational data pipelines, then delivered a multilingual document extraction pipeline now heading for production. They are today the Lead AI Engineer and second in command on AI, and they are the reason the next hire could be briefed properly.

He's realistic about the experience and skillset we actually need rather than pushing near-fits, and culturally every hire has been a good match.

Barry PryceTech Co-Founder, FleetGuru.ai
Client
FleetGuru.ai
Stage
B2B software scale-up, spun out of an established marketplace
Location
Gold Coast, Queensland
Roles
Principal Agentic AI Lead
Brief to offer
three months

Founding Forward Deployed Engineer at an agentic AI lab

An AI lab in Los Angeles working on computer use and autonomous agents hired its founding Forward Deployed Engineer through Digitalent, a role sitting between research and customer-facing delivery that draws from a very small pool.

The engineer embeds on a client site three to five days a week and owns the relationship alone, so the brief needed production-grade agentic engineering and consulting-level client handling in the same person. The company was also in stealth, which left no brand to open a conversation with, and several agencies were briefed on the same roles.

Ours was the only candidate to clear every stage, across all the agencies briefed, and the only placement any of them made. The client came back with an expanded brief of a further 8 to 12 engineers across Los Angeles and a new Manhattan office, and moved the engagement onto an exclusive footing. A single contingent hire became an ongoing partnership across both coasts.

Client
Withheld, still in stealth
Stage
Seed-stage, roughly 25 people, recently out of stealth
Location
Los Angeles
Roles
Founding Forward Deployed Engineer
Brief to shortlist
five days
Brief to offer
three and a half weeks

Also

The other areas we cover

We work across 7 areas of AI and machine learning. Most clients hire across more than one.

FAQ

Agentic AI: frequently asked questions

What Agentic AI roles do you place?
In Agentic AI we place: Heads of Agentic AI and Principal Agentic AI Leads; Agentic AI engineers with real depth in tool calling, multi-agent orchestration and state management; Forward deployed engineers who specialise in agentic AI; Applied engineers building on frontier models; Evaluation and reliability engineers; Inference and serving engineers; Post-training and fine-tuning specialists.
How quickly can you deliver a shortlist?
Brief to shortlist is approx. one week. Brief to offer is approx. three weeks for a permanent (full-time) hire and approx. one week for a contract hire.
Do you work retained or contingent?
Both, and they buy different things. Retained buys a full market map, direct approaches to people who are not looking, and sustained work on your brief alone, with the fee split in thirds: a third on engagement, a third on shortlist, a third on placement. Contingent works the reachable market quickly, with no fee until you hire someone. Payable when the candidate signs their employment contract, or on their start date. Retained suits scarce and senior hires; contingent suits most permanent (full-time) roles.

Hiring in Agentic AI?

Tell us the role and the market. A short call is usually enough to tell you what the pool looks like for it.

Hiring in the US, the UK or Australia? You will reach the person who runs searches in that market.