Campus Associate

Location: Mumbai, Maharashtra, India

Title: GIT Campus Associate

Job Summary

We are looking for an LLM-native builder to develop autonomous agentic products for our global Marketing and Sales teams. In this role, you will steer Large Language Models (LLMs) beyond simple chat, turning them into proactive "Agents" that can plan, reason, and execute multi-step tasks across our digital ecosystem. You will leverage low-code platforms for rapid orchestration while utilizing your technical full-stack depth to optimize LLM performance and build custom production wrappers. Your ultimate goal is to bridge the gap between advanced AI reasoning and real-world marketing automation and sales intelligence.

Responsibilities

- Agentic System Design Orchestration: Build and deploy autonomous agents capable of Reasoning + Action (ReAct), designing complex chains and loops using low-code tools or advanced frameworks to maintain long-running state and context.
- Prompt Architecture Tuning: Develop, iterate, and master sophisticated system prompts, few-shot examples, and structured output parsing to ensure high-quality, brand-protected outputs.
- RAG Architecture Integration: Implement and optimize Retrieval-Augmented Generation (RAG) to ground LLMs in proprietary business data, ensuring agents provide highly accurate product and sales information.
- Full-Stack Productization: Use Python and Node.js to develop the necessary glue-code, custom RESTful APIs, and frontend interfaces required to transform raw LLM workflows into polished, enterprise-ready products.
- Domain Evaluation Quality Control: Apply AI solutions directly to Marketing Automation (content generation, SEO, social listening) and Sales Intelligence while continuously evaluating outputs for alignment with "Brand Voice."
- Performance Tracking Metrics: Monitor, benchmark,



and report on LLM performance metrics, token economies, and agent accuracy to continuously refine system behavior.

Required Qualifications

- 3 Years of Engineering Experience: Strong proficiency in Python (the language of AI) and JavaScript/TypeScript, with a proven track record of building and consuming RESTful APIs.
- Hands-on AI/LLM Expertise: Deep experience working directly with frontier models (such as GPT-4o, Claude 3.5, Gemini) and a strong understanding of their specific strengths, limitations, and operational costs.
- Data Contextual Retrieval: Practical experience working with databases optimized for contextual retrieval and vector-based storage.

Preferred Qualifications

- Agentic Frameworks: Familiarity with advanced agentic concepts (Planning, Memory, Tool-use) and frameworks like LangChain, LangGraph, or CrewAI (whether implemented natively or abstracted via low-code platforms).
- Advanced Prompting Techniques: Mastery of advanced prompting methodologies, including Chain-of-Thought (CoT) and Tree-of-Thoughts (ToT).
- The "Agent-First" Mindset: Ability to view LLMs as reasoning engines rather than glorified search engines, combined with an experimental "test learn" approach to rapid AI prototyping.
- Communication Stakeholder Alignment: Strong written and verbal communication skills to effectively translate complex AI capabilities into tangible business outcomes for Sales and Marketing leadership.
- Low-Code Speed, High-Code Quality: Highly skilled at using low-code platforms for speed, but possessing the architectural depth to step into the code layer when platform limits are reached.

Experience Level

Mid Level

Disclaimer : This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Campus Associate (Maharashtra)
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