AI Engineer (Senior)

AI/ML Engineer – Context Layer & Agentic AI Developer
Location: India ( Remote)
Experience: 12-15 Years
Joining: Immediate Preferred
About the Role
We are looking for a highly skilled and hands-on AI/ML Engineer to help build next-generation
AI-powered platforms focused on Context Engineering, Agentic AI, Knowledge Graphs, and
Retrieval-Augmented Generation (RAG). He needs to lead from the front and have proactive approach. 
This role is ideal for someone passionate about building production-grade AI systems that go
beyond traditional machine learning and leverage LLMs, multi-agent orchestration, and
intelligent context layers to solve real-world business challenges. You will play a key role in
developing AI solutions that power CRM, GTM, and customer intelligence platforms for
enterprise use cases.
Key Responsibilities
● Design and develop scalable AI Context Layers that enhance reasoning and
decision-making capabilities of AI systems.
● Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector
databases, knowledge graphs, and enterprise data sources.
● Develop and deploy Agentic AI solutions and multi-agent workflows for complex
business processes.
● Design and manage integrations with LLMs, APIs, and enterprise applications.
● Build and maintain Knowledge Graphs to improve contextual understanding and AI
reasoning.
● Collaborate with product, engineering, and business teams to translate requirements into
AI-powered solutions.
● Optimize AI models and workflows for performance, scalability, security, and reliability.
● Stay current with emerging trends in Generative AI, Agent Frameworks, and AI
infrastructure.
Required Skills & Qualifications
● 12-15 years of experience in AI/ML engineering or related roles.
● Strong proficiency in Python.
● Hands-on experience with Large Language Models (LLMs) and Generative AI
applications.

● Experience building and deploying RAG architectures.
● Working knowledge of Vector Databases and Graph Databases.
● Experience with Agent Frameworks and AI orchestration platforms.
● Strong understanding of Prompt Engineering techniques.
● Experience developing and integrating RESTful APIs.
● Familiarity with cloud platforms such as AWS, Azure, or GCP.
● Strong problem-solving and system design skills.
Good to Have
● Experience with Salesforce Ecosystem, including Data Cloud and Agentforce.
● Knowledge of CRM, GTM (Go-to-Market), Sales, or Service Operations domains.
● Experience with Snowflake, Neo4j, or similar data platforms.
● Hands-on experience with LangGraph, MCP (Model Context Protocol), and
multi-agent architectures.
● Understanding of Knowledge Graphs, semantic search, and contextual intelligence
systems.
If you're excited about building intelligent systems that combine LLMs, agents,
knowledge graphs, and contextual reasoning, we'd love to hear from you.