← All jobs

Forward Deployed Engineer
Zocket
Location
Remote
Work mode
Remote
Employment
Full Time
Experience
4-10 years
About the role
Focus on customer-facing technical engagement, from pre-sales discovery and demo building to post-sales onboarding and go-live. The role involves hands-on development of custom AI agents and skills using LLMs and Python, integrating with client data sources and APIs (particularly ad-platform and analytics). It requires strong scoping discipline, technical documentation, and management of the entire enterprise customer lifecycle.
Responsibilities
- Take an enterprise prospect from first technical conversation to a live, adopted deployment: scoping what is genuinely buildable, building the demo, the custom agents and the skills yourself.
- Build and maintain custom agents and skills for the whole life of the account: writing them, wiring them to the customer's sources and connectors, testing the output quality, and deploying them.
- Run the POC and the training with the customer's day-to-day users, gather custom requirements directly, and be honest about which are configuration and which need engineering.
Full description
Forward Deployed Engineer
What you'll own
● Pre-sale, technically. Sit in discovery, work out the minimal viable setup for this prospect, then
build and run the demo yourself. You decide what is feasible; nothing enters a proposal
without your scoping behind it, and your "no" blocks the line item.
● The demo and the setup, hands-on. Configure the workspace, wire the data sources and
connectors, seed the brand knowledge, get the outputs looking like this customer's brand. Not
a spec you hand to someone — an environment you stand up.
● Custom agents and skills, for the whole life of the account. Most enterprise requirements
don't land as a feature request — they land as "our category model isn't yours", "this claim
needs a compliance check we do differently", "this report has to arrive in our format". You
build the agents and skills that close that gap: writing them, wiring them to the customer's
sources and connectors, testing the output quality, deploying them into their workspace, and
maintaining them as the requirement moves. This runs from the pre-sale demo through
onboarding and continues once they're live — it is not a one-time setup task.
● Onboarding through go-live. Run the POC and the training with the customer's day-to-day
users, not just the executive buyer. Gather custom requirements directly, and be honest about
which are configuration and which need engineering — the second kind get flagged as
roadmap evidence, never committed to a date.
● The requirements trail. Enterprise onboardings run on daily standups where asks arrive
informally, one at a time, for weeks. Keeping that legible — what was asked, by whom, what
we agreed, what the customer still owes us — is a core part of the job, not admin around it.
● The wow moment, as a number. You own the success metric for the journey from pre-sale to
go-live. It has to be measurable, falsifiable, and meaningful to the people using the product
daily — a dashboard only the buyer ever opens is a failed deployment.
● Escalations inside your window. A blocked demo, a stalled data-access request, a POC going
quiet.
Must-haves
1. You have carried enterprise customers end to end — discovery through live usage — in a
technical, customer-facing seat (forward deployed engineer, solutions/implementation
engineer, technical account or delivery engineer). Not pure pre-sale, not pure post-sale.
2. You build — including with LLMs. Comfortable in Python or an equivalent for real work: pulling
and reshaping messy client data, calling APIs, wiring integrations, standing up a demo
environment without waiting on an engineering queue. On top of that, you can build an agent
or a skill against a requirement and judge whether its output is actually good — prompting,
grounding it in the customer's own sources, evaluating quality, and iterating when it's wrong.
You will be asked to show something you built. See the stack section above for what we run —
equivalents count, exact-tool matches aren't required.
3. Scoping discipline under commercial pressure. You can say "that isn't what this does" to a
room that wants to hear yes, and can tell configuration apart from engineering on the spot.
4. You write things down clearly. Requirements, scope, escalation replies, status. Half of this job
is being the reason nobody has to reconstruct what was agreed six weeks ago.
5. Enterprise sales-cycle literacy — you have worked with security reviews, compliance sign-offs,
procurement, and customer-side stakeholders who control data access, and you route around
them without over-promising.
Nice-to-haves
● Regulated-industry deployments (BFSI, insurance, healthcare) and the compliance-boundary
instincts that come with them.
● Real depth in one of the customer-side categories above — paid media APIs, attribution, or
martech/CRM integration — rather than passing familiarity with all of them.
● Depth beyond the basics on agent tooling: multi-step/tool-using agents, retrieval design,
structured evaluation of model output rather than eyeballing it.
● Having been the first or only person in a role like this at an earlier-stage company.