Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowFirst seen 11 hours ago

Senior AI Engineer - Agentic Systems

gloat/e5.0005 open roles

Where
Israel
Work mode
Hybrid
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSenior AI Engineer - Agentic Systemsgloat/e5.000 · Israel

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on gloat/e5.000's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: first seen 11 hours ago

The posting

Gloat is the AI-native system of action for workforce orchestration. Our agentic HR platform lets enterprises build intelligent workforce agents that understand their people, respect their policies, and work where teams already are — Microsoft Teams, Slack, Google Chat, and Copilot, with no new portal or change management.

The platform is powered by Loomra, our semantic layer that connects people, jobs, and skills through a knowledge graph, deep HCM integration (Workday, SuccessFactors, Oracle HCM), a governance engine, and semantic retrieval — with a full audit trail behind every agent decision.

Trusted by 100+ enterprises across 112 countries, empowering 5M+ employees. This role sits at the center of that effort.

We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype — you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.

If you've built agents that actually made it to production — and you care as much about evaluation, guardrails, and reliability as you do about capability — we want to talk to you.

Responsibilities

  • Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
  • Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
  • Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
  • Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
  • Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
  • Optimize agents for latency, cost, and reliability at enterprise scale.
  • Take agents from prototype to production — with monitoring, observability, and a fast iteration loop.
  • Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

Requirements

  • 5+ years building production software
  • Proven experience building and shipping LLM agents to production — not just demos or prototypes.
  • Hands-on with at least one agent orchestration framework (e.g. LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or similar).
  • Strong Python and solid software engineering fundamentals.
  • Prompt engineering paired with systematic, measurable evaluation of LLM outputs.
  • Experience with tool use / function calling and integrating LLMs with external systems.
  • Track record deploying, monitoring, and maintaining AI in production (cloud, CI/CD, observability).

Nice to Have

  • 2+ years hands-on with LLMs / generative AI.
  • Practical experience with RAG, embeddings, and vector databases (e.g. pgvector, Pinecone, or similar)
  • Experience with MCP, agent memory, and planning/reasoning patterns.
  • Background in HR tech, people data, or skills ontologies.
  • Knowledge graph / graph ML experience (knowledge graphs, GNNs).
  • Responsible AI: bias evaluation, guardrails, and AI governance.
  • Experience working across multiple model providers (e.g. Anthropic, Google, IBM watsonx) rather than a single vendor.
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against gloat/e5.000's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on gloat/e5.000's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    gloat/e5.000's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.