Internship- AI & Growth Engineering Intern (AI/ML & Marketing Operations Automation)

Scalanova Health constructs AI-Native Global Capability Centers (GCCs) and Sovereign 2nd Headquarters for high-growth US Healthcare & Life Sciences companies and PE-backed platforms. We deploy dedicated practitioner-governed engineering, Clinical R&D, and RevOps pods to eliminate operational bottlenecks and build proprietary Agentic AI infrastructure.

The Role:

We are seeking an ambitious, code-first AI & Growth Engineering Intern to bridge the gap between day-to-day operations and programmatic automation. In this role, you will build internal proprietary tools, intelligent AI agents, and automated workflows that power our business operations and commercial pipeline.

This position is strictly open to recent engineering graduates (completed / B.E. / / MCA in Computer Science, Computer Engineering, AI, or Data Science) with dedicated full-time availability.

Our engineering philosophy is simple: to automate a system effectively, you must first understand how it operates manually. You will actively participate in our operational cadence—handling marketing operations, content distribution workflows, scheduling, and asset coordination. As you develop an intimate understanding of these workflows, your primary objective will be to write code, design Python scripts, deploy LLM agents, and build internal tools that automate those repetitive tasks and eliminate operational friction across our go-to-market engine.

A core prerequisite for this role is exceptional time management, high ownership, and strict adherence to project deadlines. We operate across cross-border time zones and value engineers who deliver on their commitments without requiring micromanagement.

What You Will Build:

• Operations Understanding & Execution: Support daily marketing operations, asset coordination, content scheduling, and syndication workflows across our digital channels to identify bottlenecks firsthand.

• Operations Automation: Transform manual operational and marketing routines into automated, programmatic Python workflows, webhooks, and tool integrations (connecting Zoho CRM, distribution channels, and internal databases).

• AI & LLM Automation Pipelines: Build and deploy automated micro-tools and AI agents using modern LLM APIs (OpenAI, Anthropic, Gemini, Groq, open-source models) to parse, summarize, and synthesize complex healthcare and business data into structured JSON schemas.

• Signal & Data Scrapers: Develop resilient Python-based web scrapers and trigger monitors to track public US & European Life Sciences milestones (FDA approvals, Phase II/III trial completions, VC/PE funding events, and executive hiring trends).

• Internal Product Prototyping: Build rapid, lightweight internal tools (e.g., automated prospect diagnostic audit generators, intelligent enrichment scripts, and internal knowledge bases).