AI Automation Engineer

CAI India

CAI India is a strategic investment in the company's future. Our Bangalore Center of Excellence is a place of ownership, expertise, and accountability. Teams in India work on global products end to end, contribute to key decisions, and influence how CAI evolves as a business. This is not a support-led model, but rather a center designed to lead through knowledge, responsibility, and trust.

The Role

You will be the engineer who walks into a business problem, sees the application, dashboard or integration that solves it, and builds it end to end with AI as your first tool and a full stack of skills behind it. As CAI Discrete's single, self-sufficient builder, you will work with the leaders of Support, Professional Services, Sales, Marketing, Product and Engineering to find manual, repetitive or invisible work and replace it with something that runs on its own: an AI-driven workflow on Claude and tools such as Scribe, a purpose-built internal application, a live executive dashboard, or a data pipeline connecting the systems CAI runs on — NetSuite, Salesforce and Service Cloud, Gong, Mosaic, Aha!, Jira/Azure DevOps and GitHub. This is a hands-on build role; success means things you built are in daily use, manual hours are gone and leadership decides from dashboards you created. You start as the only dedicated AI Automation Engineer in the BU; your track record is what grows the team.

What You Will Build and Do

• AI-driven automations:

  Claude-based agents and workflows that remove repetitive steps in Support and PS first, then Sales, Marketing, Product and Engineering — prompt and tool design, agentic flows, guardrails and evaluation.

• Internal applications:

  Small, purpose-built web applications where no off-the-shelf tool fits, built end to end — React or Angular front end, Python/C#/Node API, SQL database — secured with CAI's identity platform.

• Executive dashboards:

  Weekly-use dashboards for pipeline to revenue, market signals, customer health, engineering productivity and roadmap to shipped, with consistent KPI definitions and AI-generated narrative.

• Data connectivity for enterprise applications:

  Pipelines and connectors pulling enterprise-application data via APIs into a governed data layer with scheduled refresh and quality checks — internal business-system connectivity for analytics, not product integration.

• How you work:

  Scope the need with functional leaders, propose and align before building, ship with source control, CI/CD, tests and documentation, monitor in production, and quantify impact in hours saved, cycle time and adoption.

What We Are Looking For

• 6+ years of software engineering with demonstrated full-stack delivery — applications you personally built across front end, API and database and supported in production.
• Hands-on experience building automations or applied AI workflows with Claude, ChatGPT or comparable LLM tooling; demonstrated build experience, not theoretical interest.
• Proficiency in a back-end language (Python, C#/.NET or Node.js/TypeScript), a modern front-end framework (React or Angular) and SQL, including data modeling and query tuning.
• Dashboards and data pipelines: Power BI, Tableau or a code-based stack; ETL/ELT design; API integration with SaaS business applications (OAuth 2.0, webhooks, incremental extraction) — ideally two or more of NetSuite, Salesforce/Service Cloud, Gong, Mosaic, Aha!, Jira/ADO, GitHub.
• Engineering fundamentals — Git, CI/CD (Azure DevOps, GitHub Actions or Jenkins), automated testing, Azure or AWS, secure handling of credentials and data.
• Business instinct to pick problems worth solving, clear written and spoken English with non-technical stakeholders, strong self-direction across concurrent projects, and regular overlap with US business hours.

Role Parameters and Ownership

• Bangalore, India; minimum two days per week in office; no travel. Priorities and assignments from the GM, CAI Discrete Manufacturing; engineering standards and cross-BU practice with the Director of Engineering, Bangalore.
• High-ownership objectives: initial roadmap within 30 days with execution from month two; monthly status and quarterly outcome reports; hours saved as FTE-equivalent capacity is a standing measure.