Location : Ahmedabad, India – On-site Experience : 2–5 years in IT / Software Services Marketing Type : Full-time About Us We are a fast-growing IT services company specializing in dedicated developer teams and bespoke software development solutions . We help startups, IT agencies, and product-driven businesses across the globe scale faster with reliable and cost-effective tech talent. We are looking for a results-driven IT Marketer who understands funnel marketing and can generate qualified leads through digital channels, nurture them, and support our sales pipeline. 🔑 Responsibilities Design and manage end-to-end B2B marketing funnels (awareness → lead generation → nurturing → conversion). Run lead generation campaigns for dedicated developer services and custom software development . Manage and grow our LinkedIn presence through content, engagement, and outreach. Build targeted prospect lists and run cold outreach campaigns (LinkedIn + email). Develop marketing assets: case studies, email sequences, landing pages, presentations. Use Zoho CRM & Zoho Campaigns to manage leads, run automations, and track funnel performance. Research and refine ideal client profiles (ICPs) for IT agencies, startups, and product companies. ✅ Requirements 2–5 years of B2B marketing experience in IT / Software Services / SaaS . Proven experience in funnel marketing and lead nurturing strategies . Hands-on experience with Zoho CRM / Zoho Campaigns / Zoho Marketing Automation . Strong knowledge of LinkedIn marketing, cold outreach, and email automation . Excellent English communication skills (written & verbal). Ability to work full-time on-site in Ahmedabad . 🎯 What We Offer Competitive salary ( ₹4 – ₹6 LPA ). Opportunity to build and own the marketing function as we scale. 👉 If you are a funnel-focused B2B marketer with Zoho expertise and want to make an impact in the IT services industry, we’d love to hear from you!
Key Responsibilities Agentic System Design: Design, develop, and deploy autonomous AI agents capable of complex, goal-oriented reasoning, planning, and task execution using modern agentic frameworks. RAG System Development: Build and optimize robust Retrieval-Augmented Generation (RAG) pipelines to ground LLMs in proprietary data, ensuring factual accuracy and data security. Tool Integration & Function Calling: Equip AI agents with the ability to use external APIs, databases, and custom tools to perform actions in the real world. Orchestration Frameworks: Master and implement core logic using orchestration tools like LangChain, LlamaIndex, LangGraph, or CrewAI to manage conversation state and agent workflows. Prompt Engineering & Alignment: Develop systematic Prompt Engineering strategies to maximize agent reliability and output quality. Production Deployment: Develop secure, low-latency API services (using Python/FastAPI ) to serve LLM applications, ensuring high availability and scalability. Evaluation & Quality Assurance (Evals): Design and implement continuous evaluation frameworks to measure performance against business metrics. This includes developing ground truth datasets , implementing LLM-as-a-Judge scoring, and monitoring for hallucinations, factual correctness, and prompt injection . Required Skills and Qualifications Programming: 3+ years of professional software development experience, with expert proficiency in Python . LLM Application Experience: Direct experience building and deploying production-level applications using major LLM APIs or open-source models. Core RAG Expertise: Deep practical knowledge of designing, implementing, and optimizing a RAG system and proficiency with Vector Databases (e.g., Pinecone, Chroma, Milvus). Agent Orchestration: Proven experience with at least one major agent orchestration library ( LangChain, LlamaIndex, or similar state machine/graph-based frameworks ). Evaluation Tools: Hands-on experience with LLM evaluation frameworks like RAGAS, DeepEval, or LangSmith to create automated performance benchmarks. Back-end Engineering: Strong experience developing and maintaining RESTful APIs and integrating with various data sources (SQL/NoSQL). DevOps Fundamentals: Working knowledge of Docker, CI/CD pipeline and cloud infrastructure for deployment.