Senior Technical Consultant — AI Engineering & Agentic Salesforce Delivery
Salesforce · India - Bangalore
- Location
- India - Bangalore
- Funding
- ~$184.9B
- Posted
- Sep 9, 2026
Salesforce is hiring a Senior Technical Consultant — AI Engineering & Agentic Salesforce Delivery based in India - Bangalore. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.
Apply directly at SalesforceRole details
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Customer Success Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. About the Role The Senior Technical Consultant is a hands-on technical role spanning AI platform engineering and Salesforce project delivery . The role will contribute to building and enhancing the organization's multi-agent AI delivery platform, while also using the platform and agentic development approaches to deliver Salesforce projects. The platform brings together multiple LLMs, public AI models, agents, tools, and workflows to support the Salesforce delivery lifecycle. The Senior Technical Consultant will help evolve these capabilities, support projects adopting the platform, and work as a senior Salesforce developer on delivery projects using AI-first and agentic development practices . The ideal candidate combines strong Salesforce engineering expertise with AI/LLM and agentic development skills , and can build solutions, solve complex problems, and guide other developers in adopting new ways of working. Key Responsibilities AI Platform Engineering Develop and enhance the organization's multi-agent AI application , including agents, tools, workflows, integrations, and automations. Work with multiple LLMs and public AI models and evaluate their suitability for different use cases. Implement agent orchestration, tool use, prompting, context management, grounding, and workflow execution. Build reusable AI capabilities that can be leveraged across Salesforce projects. Prototype new AI capabilities and convert successful PoCs into production-ready solutions. Continuously experiment with emerging AI frameworks, models, and developer tools. Agentic Salesforce Delivery Work as a Senior Resource on delivery projects, using AI and agentic development approaches to accelerate and improve delivery. Use the AI platform and associated agents, tools, and workflows across the Salesforce development lifecycle. Apply agentic approaches to activities including analysis, design, coding, testing, troubleshooting, documentation, and deployment . Build and review Salesforce solutions using Apex, LWC, Flow, integrations, APIs, and other Salesforce technologies. Ensure AI-assisted and AI-generated solutions meet Salesforce architecture, security, quality, and engineering standards. Identify opportunities within projects to automate repetitive development activities and improve developer productivity. Platform Support & Problem Solving Support Salesforce projects using the AI delivery platform and resolve incoming technical issues. Diagnose problems across the application, agents, LLMs, prompts, tools, integrations, and Salesforce components. Work with Technical Architects and the AI application owner to identify root causes and implement sustainable fixes. Identify recurring project issues and convert solutions into reusable platform capabilities. Feed project experience and user feedback into continuous improvement of the AI platform. Enablement & Technical Leadership Guide Salesforce developers and project teams in agentic ways of working and AI-assisted development . Help teams understand how and when to use agents, AI tools, and platform capabilities effectively. Establish and share practical patterns, best practices, and lessons learned from real project delivery. Collaborate with Technical Architects and the AI application owner to drive adoption and improve delivery outcomes. Builder & Engineering Mindset Be a hands-on developer who builds and ships working solutions , rather than primarily a design/documentation role. Use AI-assisted development tools such as Claude Code, Cursor, Gemini, and similar tools . Follow modern engineering practices including Git, CI/CD, testing, code reviews, and maintainable design. Balance rapid experimentation with scalability, security, reliability, and production quality. Preferred Qualifications 5–7 years of Salesforce/software engineering experience with strong hands-on Salesforce development skills. Strong experience with Apex, LWC, SOQL, Flow, APIs, integrations, and Salesforce metadata . Experience building multi-agent or agentic AI applications . Experience working with multiple LLM providers/models. Experience with MCP, agent orchestration, RAG, vector search, or LLM evaluation . Hands-on experience with Claude Code, Cursor, Gemini, or similar AI coding tools . Experience integrating AI applications with Salesforce APIs, metadata, repositories, or development environments. Experience with Agentforce or other enterprise AI/agent platforms. Salesforce certifications such as Platform Developer II, Application Architect, or System Architect. Key Attributes Builder: Comfortable building and shipping both Salesforce and AI solutions. AI Practitioner: Uses AI and agentic approaches as part of day-to-day development. Salesforce Technologist: Strong understanding of enterprise Salesforce development and architecture. Problem Solver: Can debug issues across AI, application, integration, and Salesforce layers. Enabler: Helps other developers and teams adopt agentic ways of working. Product Mindset: Turns project learnings into reusable platform capabilities. Collaborator: Works closely with architects, the AI platform owner, and delivery teams. Success in the Rol
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