Position summary The AI Automation Engineer is responsible for the design, development and deployment of internal applications that reduce manual effort across the organisation. The role is one of applied engineering rather than research or model development, and requires close collaboration with the merchandising, production, sourcing, human resources, compliance and sustainability functions.

The postholder can expect to deliver several production tools each quarter, alongside the iterative refinement and, where appropriate, retirement of existing solutions as business processes evolve.

Indicative projects

Representative initiatives from the current development pipeline:

ERP intelligence layer (WFX). Conversational access to order status, enabling merchandising teams to identify at-risk purchase orders without compiling multiple reports.

Email and document automation. Automated triage, extraction and routing of buyer correspondence, including tech packs, purchase order amendments and compliance requests, with drafted responses.

Compliance documentation pipelines. Automated preparation of traceability and audit evidence in buyer-specified formats, replacing current manual processes.

Design archive search. Image tagging and semantic search across the design library, enabling retrieval by visual and material attributes.

ESG and GHG data pipelines. Consolidation of utility, fuel and production data into emissions calculations, supported by a verifiable audit trail.

Production reporting. Consolidated production, efficiency and quality metrics, optimised for mobile access by plant leadership.

Key responsibilities

Engage directly with operational teams to document existing manual processes and assess automation viability and priority.

Develop and deploy internal applications end to end, encompassing backend services, user interfaces,



authentication and error handling.

Design agent workflows and system integrations, including MCP servers, API connectors, retrieval-augmented generation pipelines, and structured extraction from documents and images.

Assume responsibility for deployment and operational uptime across VPS and cloud environments.

Prepare technical documentation and deliver user training to support adoption across departments.

Monitor operating cost per workflow and recommend discontinuation where returns do not justify continued investment.

Essential requirements

Two to five years of experience in software development and delivery, including recent production experience with large language model APIs.

Proficiency in TypeScript/Node or Python, with working familiarity in the other.

Demonstrated delivery of an LLM-based application in sustained use, covering prompt design, tool and function calling, structured outputs, and evaluation methodology.

Experience with APIs, webhooks, authentication protocols and third-party system integration.

Ability to develop functional user interfaces (React or equivalent).

Working knowledge of SQL and experience handling inconsistent or unstructured data.

Competence in deployment fundamentals: Linux, Docker, environment configuration and logging.

Strong communication skills, with a demonstrated ability to elicit requirements from non-technical stakeholders in an operational setting.

Desirable experience

Exposure to manufacturing, apparel, textile or supply chain systems, including ERP, PLM or shop floor applications.

Vector databases and retrieval pipelines; document AI, including OCR, layout parsing and extraction from scanned documents.

Computer vision applications for image classification and search.

Familiarity with MCP, agent frameworks or agentic development tools.

Exposure to ESG, sustainability or compliance reporting.

📌 AI Automation Engineer (Gurugram)
🏢 WOW Softech
📍 Gurugram