דרושים » AI » דרוש /ה AI Engineer

Alice is building its internal AI infrastructure layer from the ground up. We have real agents running in production, a growing base of employees using AI in their daily work, and a clear architectural direction. What we don't have yet is a dedicated engineer to own it. You'll be the first. Your job is to close the gap between "working prototype" and "production platform" - owning the foundation that hosts our agents, the pipelines that ship them, and the reliability layer (observability, cost controls, audit trails, evals) that makes it safe to run AI at scale in a trust & safety company. This is an infrastructure-first role with deep AI fluency - not a prompt engineer, not a wrapper-framework operator, not a no-code builder. You should be equally comfortable writing a Terraform module, debugging a Kubernetes pod, and tracing an agent's tool-call chain. We don’t operate with a predefined backlog here; you will be responsible for identifying high-impact needs and bringing them to life. The perfect fit for this role has a track record of deploying agentic systems that have held up under real-world usage, balances a focus on infrastructure with a deep concern for user experience, and recognizes that the primary hurdle in AI integration is rarely the model itself. Responsibilities: Platform & Infrastructure
* Architect, build, and run the AWS/Kubernetes platform that hosts Alice's internal AI agents and tools; drive AWS Well-Architected pillars (operational excellence, security, reliability, performance, cost, sustainability).
* Own Infrastructure-as-Code: Terraform modules, standards, and reviews for Bedrock, agent runtimes, vector DBs, and supporting services. AI Systems
* Design and ship production-grade agents and multi-agent pipelines using the Anthropic Agent SDK, Claude Code, AWS Bedrock, and MCP — not wrapper frameworks.
* Own the full agent lifecycle: scoping ? prototyping ? eval ? deploy ? monitor ? iterate.
* Integrate agentic workflows into internal and product systems via APIs, databases, webhooks, Slack, and email. Reliability, Observability, Cost
* Build first-class observability across apps and infra: OpenTelemetry, Prometheus, plus LLM-specific tracing (Langfuse or equivalent), token/cost metrics, and eval pipelines.
* Define SLOs/SLIs and error budgets for AI services - latency, model fallback chains, eval regression gates, agent success rates. Lead incident readiness, response, and post-mortems.
* Drive FinOps: model routing by cost, cache hit rates, batch vs. realtime tradeoffs, budget alarms, per-team chargeback visibility.
* Implement guardrails: prompt-injection defenses, PII redaction, model allowlists, human-in-the-loop checkpoints, audit trails. Org Impact
* Identify high-leverage workflows across the organization and translate them into scalable agentic automations.
* Partner with R&D, Delivery, security, and external vendors to deliver platform capabilities.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

Hybrid:
Yes

As we scale our portfolio of live automations, were looking for an experienced AI Automation & Agent Engineer to take on a broad and high-impact role. Youll lead new automation projects from ideation to production, own the reliability of existing systems, and serve as the go-to expert helping our employees get the most out of AI tools - especially Claude Code. This is a hands-on, cross-functional position at the center of how we adopt and scale AI internally.
Responsibilities
Lead Automation Projects:
Partner with department leads across sales, support, finance, and HR to identify high-impact AI and automation opportunities.
Design and build LLM-based workflows, integrating APIs, MCP servers, and internal tools.
Develop agent-like automations and internal copilots that augment decision-making and execution.
Own the full lifecycle - from ideation and process design through development, testing, and production launch.
Present project plans, progress updates, and outcomes with measurable impact to stakeholders at all levels.
Build AI Systems & Integrations:
Build robust, maintainable workflows using N8N, Claude Code, and other orchestration tools.
Integrate across systems using REST APIs, webhooks, and external/internal tools.
Design reusable patterns for skills, agents, and workflows that can scale across teams.
Continuously evaluate and adopt new AI tooling, MCP capabilities, and agent frameworks.
Maintain & Improve Live Systems:
Monitor, triage, and resolve issues across all live AI automations, copilots, and agents.
Identify recurring failure patterns and implement systemic improvements to reliability, performance, and cost.
Ship incremental improvements and new capabilities quickly and safely.
Maintain clear documentation for workflows, agents, and system behavior.
Drive AI Adoption, Skills & Governance Across:
Act as the internal expert and first point of contact for employees using Claude Code and AI tools.
Help teams build and scale AI skills - from basic usage to advanced workflows and agent design.
Manage and optimize AI usage and performance across the organization (tokens, costs, reliability, adoption).
Build and evolve an internal AI control tower - providing visibility into usage, performance, governance, and impact.
Run onboarding sessions, workshops, and create practical guides that empower teams to work independently with AI.
Guide teams through MCP integrations, tool configurations, and best practices.
Stay current on Claude Code updates, new MCP capabilities, and emerging AI tooling - and proactively share relevant developments with the team.

Were looking for a hands-on, entrepreneurial Team Lead to take full ownership of Ollys knowledge systems and build one of the most critical pillars of the product.

Responsibilities

Technical and managerial leadership of the Knowledge team
Designing and building production-grade knowledge systems at scale
Making architectural decisions and tradeoffs
(LLMs vs embeddings vs heuristics, online vs offline computation, cost vs latency)
Driving research, experimentation, and innovation around what knowledge means for AI Agents
Hiring, interviewing, mentoring, and growing the team
Working closely with Agent, Platform, and Product teams