[Hiring] Senior Agentic Backend Engineer @beqom

Role Description

We are looking for a Senior Agentic Backend Engineer to join our Data Platform Core team, which owns the services at the heart of beqom’s data architecture — multi-tenant data ingestion, schema management, snapshots, calculated fields, and the data contracts powering analytics and reporting across the product.

In this role you will not write the code. AI agents will. You will own the specifications that govern these services, the agentic pipeline that turns those specifications into production software, and the verification machinery that proves the output is correct — with the explicit goal of reaching fully AI-embedded development: no human-written code, no human line-by-line review, and external behavioural scenarios, not traditional test suites, as the quality gate.

You will collaborate closely with Data Platform and Analytics engineers, Support teams, and Product stakeholders — translating their needs into agent-executable specifications. Specs are our system of record; agents do the typing.

Qualifications

• Demonstrated senior-level experience building production backend services — including .NET/C# and PostgreSQL systems.
• Hands-on mastery of AI coding agents — Claude Code strongly preferred.
• Excellence in specification writing — turning ambiguous business needs into precise, agent-executable PRPs and spec files.
• Strong verification engineering: behavioural and scenario-based testing, holdout evaluation, quality gates, and validation frameworks.
• Strong architecture judgement: assessing whether an agent-proposed solution meets performance, scalability, and reliability requirements.
• Experience building agent infrastructure: MCP servers and tool layers, sandboxed execution, and CI/CD adapted for agent-driven workflows.
• Deep enough .NET/C# and SQL reading fluency to audit generated code when quality gates flag it.
• Excellent written communication: specs, scenario definitions, and design docs that both humans and agents can act on.

Requirements

• Run multiple agents in parallel across workstreams; evaluate outcomes against specs.
• Progress agent first-pass success rate, defect escape rate, and the share of changes merged without human review steadily upward.
• Build and maintain the agentic pipeline: agent harness, blueprint engine interleaving deterministic steps with AI reasoning.
• Own the economics of the pipeline: observability over token usage, task latency, and cost per run.
• Embed governance into the pipeline — machine-generated audit trails, named ownership per feature.
• Engineer verification, not code: external behavioural scenario suites and holdout sets stored outside the codebase.
• Set and enforce the constraints that keep agent output correct on performance-critical paths.
• Diagnose and resolve production data issues through agents.
• Document the specs, scenarios, and pipeline decisions that govern the platform.

Benefits

• Your career, your design. Unleash your ambition in our dynamic, autonomous environment.
• Drive meaningful change. Build a fairer future for every employee by joining a market leader that is improving the world of work.
• Belong to something bigger. Collaborate with a passionate, diverse and talented team around the globe.