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About the Company
Solutions Engineer (AI, Identity & Data Security) Location: [India] Minimum Experience: 8+ years in Pre-Sales/ Solution Engineering or a similar senior technical customer-facing role
About the Role
The Sales Engineer is the technical authority and narrative driver in customer engagements. This role is responsible for translating complex AI, Identity, and Data Protection challenges into defensible, real-world solutions—while helping customers understand not just how something works, but why it matters. This role blends deep hands-on technical expertise with storytelling, big-picture (paint the picture) thinking, and collaborative problem solving. You will work with prospects to obtain the technical win by designing a viable technical solution with an amazing product that can be applied to various scenarios. You will operate across AI security, LLMs, AI agents, MCP, DLP, and Identity, partnering closely with Sales, Product, and Engineering to close deals and influence product direction.
Responsibilities
Technical Discovery & Storytelling
Architecture & Solution Design
Workshops & Collaborative Problem Solving
Execution & Field Innovation
Qualifications
What Success Looks Like
Job ID: 153806161
Skills:
.Net 10, Power Bi, Power Automate, Sql, Angular, React, Python, Power Apps, LLM model, Azure services, Microsoft Power Platform, NoSQL Database
Skills:
Tensorflow, Pytorch, Gcp, Cloud Architecture, Azure, Python, AWS, langgraph, LLMs, cloud-native architecture, ML models, langchain, SRE tools, full stack IT operations, AI ML services, AI agents, AI generative, Agentic
Skills:
PostgreSQL, Numpy, Git, Pandas, Pytorch, Docker, FastAPI, Rest Apis, Python, Kubernetes, LangChain, Anthropic Claude, scikit-learn, pgvector, Qdrant, MLflow, Azure OpenAI, LangGraph, Ollama, Kubeflow
Skills:
.NET, Data Modeling, Debugging, Rest Apis, Ms Sql Server, Validation, RAG pipelines, Localization, Lang Chain, automated content-generation systems, Semantic Kernel, AI agents, Azure OpenAI, Optimization, Inriver Inspire AI, enrichment workflows, Azure AI Orchestration, Taxonomy
Skills:
Machine Learning, Sql, Azure Sql, Numpy, Django, Git, Pandas, Azure Functions, Docker, Flask, Microsoft Azure, FastAPI, Rest Apis, Data Analytics, Python, Azure DevOps, Scikit-learn, App Service, CI CD pipelines