---
title: 'Agentic AI Automation Engineer at HRS'
canonical: 'https://feeny.ai/job/agentic-ai-automation-engineer-hrs-mohali-v94kjndfpf05'
type: 'job'
last_seen: '2026-10-12'
---

# Agentic AI Automation Engineer at HRS

- **Company:** HRS
- **Location:** Mohali, India
- **Employment:** full-time
- **Posted:** 2026-09-25
- **Last confirmed live:** 2026-10-12
- **Apply:** https://jobs.ashbyhq.com/hrs/52fa1cba-5d9d-473c-989c-798a4966040d

## Job description

Mid-Level AI Engineer — Agentic AI AI-Workflow Programme | Mohali, On-Site

## POSITION

We are seeking a Mid-Level AI Agentic Engineer to join the AI-Workflow programme and build the autonomous crew systems that augment HRS operations across Finance, Controlling, Operations, Customer Service, Customer Experience, and HR. This is not a research role or a prototype environment — you will be building production AI crews that handle live operational workflows for real departments, with real outcomes measured from day one. You will work within a "crews building crews" model: a platform of seven build agents (PM, Architect, Automation, QA, SRE, Documentation, Observability) scaffolds, tests, and documents the operational crews you build. Your job is to close the gap between agent scaffolded output and production-ready code — working directly with the Tech Lead, the PM, and the build agent platform to deliver tested, instrumented, and documented crews within a 10-day delivery lifecycle. The mission is workforce augmentation. AI handles the volume. Humans handle the judgement. Every crew you build encodes that principle in every escalation boundary, every guardrail, and every human-in-the-loop gate.

## CHALLENGE

Crew Development & Implementation

- Build operational AI crews from structured To-Be process descriptions using DSPy typed signatures with assertion guards and agent workflow orchestration patterns such as state machines, human-in-the-loop checkpoints, and resumable execution
- Implement N8N workflow automation and JSON integration connectors linking crews to operational systems including Zammad, Genesys, and enterprise back office platforms
- Work directly with the Automation Agent to scaffold DSPy modules and agent workflows — extending and improving generated output, not accepting it verbatim
- Design and encode specific, testable escalation boundaries for every crew before shadow deployment — grounded in real process context, not generic confidence thresholds
- Deliver every crew with 100% unit test coverage, a complete runbook, and New Relic instrumentation live before go-live — these are deployment gates, not aspirational standards
- Contribute reusable patterns to the shared crew library and peer-review modules built by other engineers on the team Technical Execution & Quality
- Implement agent memory management using explicit typed state, structured context handling, and clear handoff boundaries to prevent context degradation across multi-step operational workflows
- Apply three-layer output validation — DSPy assertions, output validators, and policy enforcer — on every crew module before merge
- Build and validate test suites covering non-deterministic edge cases and failure modes — not just happy paths — using the QA Agent's generated baseline as a starting point
- Integrate crews with AWS Bedrock model routing (Claude Haiku/Sonnet) and work within the EKS and Terraform IaC stack managed by DevOps
- Maintain guardrails configuration for every crew — escalation triggers, human approval gates, and policy enforcement — encoded in config before any crew enters shadow deployment
- Participate in weekly DSPy evaluation cycles against gold-standard baselines to validate crew output quality and flag drift Observability & Production Operations
- Instrument every crew with New Relic metrics from day one: throughput, error rate, latency, escalation rate, and cost per task — observability is a deployment prerequisite, not an afterthought
- Actively diagnose and resolve production failure modes: memory drift across multi step workflows, hallucination under low-confidence RAG retrieval, context degradation in long-running state machines, and prompt injection via untrusted integration inputs
- Use post-deployment observability data to identify improvement candidates and raise them in RAID — closing the feedback loop the Observability Agent depends on
- Contribute to the continuous improvement cycle: every crew in production is a measurement and improvement loop, not a delivery milestone Collaboration & Build Platform
- Work within the 10-day delivery lifecycle — Request → Discovery → Design → Development → QA → CI/CD → Monitoring → Continuous Improvement — delivering to standard at each stage
- Collaborate with the PM during Discovery to assess process automation feasibility using FUDV scoring — frequency, uniformity, digitisation, volume — and push back credibly where AI reliability or data quality is not there yet
- Contribute to Thursday technical reviews and Friday retrospectives with substantive input — not status updates but engineering judgment
- Use the build agent platform as a personal productivity multiplier — flag platform gaps via RAID rather than working around them silently FOR THIS EXCITING MISSION YOU ARE EQUIPPED WITH… Agentic AI Technical Skills
- 3–5 years of experience in AI/ML development with 1+ years in agentic AI or advanced LLM applications shipped to a production environment — not prototype or hackathon experience
- Hands-on experience with DSPy typed signatures and assertion guards — not just LangChain familiarity
- Practical exposure to at least one agent framework or platform such as LangGraph, Google ADK, Amazon Bedrock AgentCore, LangChain, CrewAI, or equivalent; the role values transferable agentic engineering patterns over any single required framework
- Experience building and committing N8N workflow automation in a production codebase
- Demonstrated ability to design specific, testable escalation boundaries in a live operational AI system
- Can show their work — a GitHub profile, a shipped system, or a concrete before/after on a workflow they automated carries more weight than academic credentials AI Engineering Capabilities
- Strong Python programming skills with AI/ML libraries and practical agentic engineering patterns; able to work across frameworks when needed, with exposure to at least one of LangGraph, Google ADK, Amazon Bedrock AgentCore, LangChain, CrewAI, or equivalent
- Production experience with AWS Bedrock or equivalent cloud-based LLM routing and model management
- Knowledge of vector databases, embedding systems, and retrieval-augmented generation — including retrieval quality assessment and hallucination mitigation
- Understanding of MLOps and AIOps practices: CI/CD for AI systems, evaluation harnesses, and gold-standard baseline testing
- Hands-on experience with New Relic or equivalent observability tooling for production AI systems — metric design, dashboard instrumentation, and anomaly diagnosis
- Familiarity with containerisation, EKS, and Terraform IaC sufficient to work within a DevOps-managed infrastructure without creating integration delays Development & Process Skills
- Test-driven development for non-deterministic systems — 100% unit test coverage before merge is a non-negotiable standard in this team
- Experience with agile delivery in a timeboxed sprint model — able to take a structured process description from design to shadow deployment within a 10-day lifecycle
- Strong code documentation discipline — every module peer-handoff ready, every runbook complete during build, every decision traceable in RAID
- Ability to work within an architecture set by a Tech Lead — executing with full ownership and quality pride within defined guardrails, escalating cleanly when constraints need revisiting Professional Skills
- Writes to be understood, not to be impressive — RAID entries a director can triage, runbooks a department SME can follow, code a peer can extend without asking the author
- Calm under non-determinism — diagnoses production failures methodically using observability data rather than thrashing or going silent
- Dog-food mentality — uses the build agent platform to accelerate their own work and actively contributes to improving it
- Mission-driven — understands that the goal is workforce augmentation, not automation for its own sake, and builds every crew with that principle at its centre

## Preferred Experience

- Domain experience in at least one of: Finance, Controlling, HR, Operations, Customer Service, or Customer Experience — brings escalation boundary instinct that no intake card can fully replicate
- Experience with enterprise system integrations: Zammad, Genesys, UiPath, or equivalent CRM/CX/RPA platforms
- Familiarity with ChromaDB/Milvus/pgVector or equivalent vector store for RAG pipeline development
- Experience contributing to a shared pattern library or internal engineering knowledge base in a multi-engineer AI team

## About HRS

## Company Overview
- **One-liner**: HRS is a global technology platform that reimagines corporate lodging and meetings management through an AI-powered end-to-end SaaS solution.
- **Entity Type**: Private (Bootstrapped, owned by CEO Tobias Ragge)
- **Headquarters**: Cologne, Germany
- **Founded**: 1972
- **Founders**: Founded as a regional reservation service; current CEO and owner is Tobias Ragge

## Core Business
- **Primary Industry**: Corporate travel management (lodging and meetings), Fintech (payment solutions), Sustainability tech (Green Stay Initiative)
- **Target Customers**: B2B — Enterprise (Fortune 500), SMBs, and business travelers
- **Mission/Purpose**: "To reinvent the way business travelers can STAY, WORK and PAY" by challenging legacy structures and over-engineered ecosystems.

## Products & Services
- **[HRS Connect](https://corporate.hrs.com/)**: An all-in-one booking and procurement platform for lodging (transient, groups, longstay) and meetings. It connects to GDS, non-GDS, OTA, and direct inventory, automates rate filtering, rebooking, payment, and invoicing.
- **[HRS Copilot](https://corporate.hrs.com/)**: A patent-pending AI-powered assistant that provides real-time, data-driven recommendations to optimize savings, compliance, traveler satisfaction, and carbon emissions. Integrates with existing tech stacks and expense systems.
- **[HRS Green Stay](https://corporate.hrs.com/)**: An ISO 14067-certified initiative that provides science-based property-level data on water, waste, and energy consumption, enabling companies to report, reduce, and remove CO₂ emissions from hotel stays. HRS is a Climate Pledge signatory.
- **[HRS Payment Solutions](https://corporate.hrs.com/)**: Automated payment and invoicing tools that include VAT reclaim, line-item invoice data, and credit card rebate optimization.

## Market Standing
- **Valuation**: Not publicly available (privately held by CEO)
- **Key Metric**: Annual Revenue not disclosed; the company serves **35% of Fortune 500 companies** [corporate.hrs.com](https://corporate.hrs.com/).
- **Notable Investors/Partners**: HRS is privately owned. It partners with 200+ solutions (TMCs, OBTs, expense and payment systems). Strategic equity investment in Itelya for integrated payment solutions.
- **Growth Signals**:
    - Recognized among **Germany’s TOP 100 Most Innovative Companies** [corporate.hrs.com](https://corporate.hrs.com/about).
    - Member of the **Global Sustainable Tourism Council**.
    - **EcoVadis Bronze Medal** (top 35% globally) for sustainability management.
    - Operates in **30 markets** globally including London, Milan, Mumbai, New York, Paris, San Francisco, Seoul, Tokyo, and Sydney [jobs.hrs.com](https://jobs.hrs.com/content/Our-history/?locale=en_US).

## Competitive Advantages
- **Data-First Moat**: Their patented rate filter, automated rebooking, and Copilot AI generate unique, actionable data that creates lock-in with enterprise clients.
- **End-to-End Automation**: Unlike traditional TMCs, HRS offers a fully automated process from procurement to payment and reclaim, reducing manual work and delivering VAT rebates.
- **Sustainability Standard-Setting**: The Green Stay Initiative is a first-of-its-kind, science-based, ISO-certified tool that directly ties sustainability data into procurement decisions.
- **50-Year Heritage + Startup Agility**: Described as a "50-year-old start-up," they combine the stability of a mature company with the innovation culture of a tech firm.

## Strategic Focus
- **AI-First Transformation**: Deepening the role of Copilot to move from a booking tool to a strategic decision-making assistant for travel and procurement managers.
- **Fintech Expansion**: Integrating payment and invoicing deeper into the platform to create a unified "stay, work, pay" experience (e.g., investment in Itelya).
- **Net-Zero Leadership**: Pledging net-zero carbon emissions by 2040 (a decade ahead of the Paris Agreement) and scaling the Green Stay initiative globally.
- **Platform Convergence**: Unifying lodging, meetings, and longstay under a single, seamless interface to increase adoption and spend visibility.

## Why Work Here
- **Culture**: Described as a "tribe of Intrapreneurs" with a focus on entrepreneurship, passion, enthusiasm, and teaming. The CEO Tobias Ragge says: "Be a missionary, work hard, have fun, and make history" [jobs.hrs.com](https://jobs.hrs.com/content/Culture/?locale=en_US).
- **Diversity**: Over **850 employees** representing **57 nationalities**, with a strong emphasis on DEI (Diversity, Equity, Inclusion) [jobs.hrs.com](https://jobs.hrs.com/content/Culture/?locale=en_US).
- **Remote/Hybrid Policy**: Not explicitly stated as fully remote. The company operates from 30+ global markets (Cologne HQ, London, New York, San Francisco, etc.), suggesting a hybrid or in-office collaborative environment depending on role.
- **Perks & Engineering Culture**:
    - Ranked among Germany’s TOP 100 most innovative companies, indicating strong R&D and engineering investment.
    - Culture of "learning from failure and scaling through operational excellence."
    - Opportunity to work on cutting-edge AI, fintech, and sustainability solutions at a global scale.
    - Young, agile environment with a 50-year history of stability.

## Sources
1. [corporate.hrs.com](https://corporate.hrs.com/) – Official corporate site (products, mission, partners)
2. [corporate.hrs.com/about](https://corporate.hrs.com/about) – About page (history, leadership, sustainability, DEI)
3. [jobs.hrs.com](https://jobs.hrs.com/content/Culture/?locale=en_US) – Culture and careers page
4. [jobs.hrs.com](https://jobs.hrs.com/content/Our-history/?locale=en_US) – History & team success factors
5. [jobs.ashbyhq.com/hrs](https://jobs.ashbyhq.com/hrs) – Official careers portal (Ashby)

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