Overview

About Us: Xpedeon is an integrated purpose-built ERP Suite contributing to digital transformation in the construction and engineering industry across the globe.

Responsibilities

• Design and build multi-step agent execution loops that plan, call tools/APIs, observe results, and adapt not single-shot prompt/response.
• Build the tool-calling layer: define what actions an agent can take, with strict schemas and validation on every tool invocation before it executes.
• Design authorization and scoping so an agent can only take actions within an explicit, auditable allowlist never inferring permission from context or "the user probably meant."
• Build human-in-the-loop approval flows: identify which actions are safe to auto-execute versus which require explicit user/operator confirmation before running and design the UX/API for that checkpoint.
• Design for partial failure: make multi-step tasks idempotent and resumable, so a crash or timeout mid-task doesn't leave data in an inconsistent or duplicated state and build rollback/compensating actions where true undo isn't possible.
• Build comprehensive audit logging of every action an agent takes what it decided, what tool it called, what the result was, and why sufficient to reconstruct and explain any outcome after the fact.
• Implement rate limiting, circuit breakers, and hard stop conditions so a misbehaving agent loop can't run away (excessive retries, repeated failed actions, runaway cost/API usage).
• Write test suites that simulate multi-step task execution, including deliberate failure injection at each step, to prove the agent handles partial failure and unauthorized-action attempts correctly not just that the happy path works.
• Collaborate with product/ops stakeholders to define which actions are in scope for automation at all, and which should remain human-only regardless of technical feasibility.
• Monitor agents in production for anomalous behavior (unexpected tool calls, repeated failures, actions outside historical patterns) and build alerting around it.

Qualifications

• 3+ years of professional software engineering experience, with strong backend proficiency (Python or comparable).
• Hands-on experience with LLM tool-calling/function-calling APIs and building the orchestration logic around them (not just prompting a chat model).
• Strong instincts for failure-mode thinking given any action, can you name what goes wrong if it runs twice, runs out of order, or fails halfway and design for it up front.
• Clear written communication comfortable documenting which actions are explicitly out of scope for automation and why, not just what the agent can do.
• Background in a regulated or high-stakes automation domain (fintech, healthcare ops, infra/SRE automation) where "irreversible action taken incorrectly" has real cost.
• Familiarity with our existing read-only AI pipeline (RAG/retrieval-based Q&A) useful for context, not required, since this role's core skills are distinct from that track.
• Prompt-engineering-only experience without systems/backend engineering depth.
• Comfort automating actions without designing explicit guardrails first this role requires a "prove it's safe" default, not a "ship it and monitor" default.
• Ship one end-to-end automated action (or a scoped subset of one) with an explicit permission boundary, idempotency handling, and full audit logging in production.
• Deliver a failure-injection test suite for at least one multi-step task that proves correct behavior under partial failure.
• Define and document, with product/ops input, the current allowlist/denylist of actions the agent is authorized to take and the escalation path for anything outside it.
• Mid-level: implements individual tool integrations and action flows under an established authorization/approval framework.
• Senior/lead: owns the authorization model, approval-flow architecture, and failure-handling standards as the set of automatable actions grows; makes the call on what should never be automated.