Software Engineering MTS (Full Stack) - AI Generalist (Demo Tools & Platform Engineering)

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Software Engineering MTS (Full Stack) - AI Generalist (Demo Tools & Platform Engineering)

Salesforce

Hyderabad

4-6 years

Today

$44.6K–62.7K/yr

Full-time

Onsite

Skills Required LLM

RAG

LangChain

AutoGPT

Vector Database

Embeddings

Pinecone

Weaviate

Slack APIs

Slack bots

Salesforce platforms

React

Angular

Vue.js

Node.js

Description Salesforce is a leading AI CRM company focused on innovation and workforce transformation. The role involves building AI-powered internal platforms that support demo experiences across products and industries.

Company: Salesforce

Role: Member of Technical Staff (MTS)

Experience

• 4–6 years of professional software development experience

Responsibilities

• Design and build full-stack applications (frontend and backend) for internal AI-powered tools
• Develop and maintain scalable backend services, APIs, and microservices
• Build and integrate LLM-powered agents into internal workflows including automation, orchestration, and task execution
• Design and implement reusable skills/tools that agents can invoke to interact with internal systems
• Build Slack-based tools, bots, and AI-driven workflows for self-service and automation
• Implement retrieval-augmented systems (RAG), embeddings, and context-aware data pipelines
• Work across frontend (Angular, Vue, React or similar) and backend (Node.js/Python) to deliver end-to-end experiences
• Write clean, maintainable, and scalable code with strong focus on reliability and observability
• Participate in design discussions, code reviews, and technical decision-making
• Partner closely with product managers, designers, and engineers to ship impactful solutions
• Continuously evaluate and improve system performance, cost, and developer experience

Additional Responsibilities

• Ability to take ownership from design through production in ambiguous environments
• Strong understanding of version control (Git) and collaborative workflows
• Familiarity with data handling for AI systems including structured/unstructured data, APIs, and storage

Nice To Have

• Experience with agent frameworks such as LangChain or AutoGPT
• Experience with vector databases such as Pinecone or Weaviate
• Experience building RAG pipelines and context-aware AI systems
• Familiarity with Slack APIs, bots, and conversational interfaces
• Experience working with Salesforce platforms including Sales, Service, Experience Cloud, Data Cloud, Agentforce
• Experience building internal developer platforms or enablement tooling
• Awareness of AI system risks such as prompt injection, data leakage, and reliability issues

More Skills JavaScript, TypeScript, Python, RESTful APIs, microservices, LLM APIs, Git, distributed systems, system design, software engineering

Prepare for this role

Recommended resources to build the skills for this position. Sponsored.

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Top 15 Embeddings Interview Questions (Quick)

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