Salesforce Architect

NTT DATA BUSINESS SOLUTIONS; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS seeks a Salesforce Architect to join our Bangalore, Karnataka team. You will own end-to-end solution architecture across Agentforce, Salesforce CPQ and Revenue Cloud Advanced, and lead integration patterns with MuleSoft, APIs, and external services.

Responsibilities include designing multi-agent workflows, context engineering, and secure action patterns, with mentoring of architects and developers. Strong communication to stakeholders is required.

Qualifications

• Extensive Salesforce CPQ/Revenue Cloud architecture experience.
• Proven ability to design agent-based architecture patterns.
• Strong integration experience with MuleSoft and APIs.

Responsibilities

• Own end-to-end solution architecture across Agentforce, CPQ, Revenue Cloud.
• Design multi-agent workflows and orchestration patterns across lifecycle processes.
• Architect integration of Agentforce with Salesforce automation, APIs and enterprise services.
• Define AI safety, grounding, and effective use of non-generative solutions.
• Lead architecture governance and mentor engineers across delivery teams.

Skills

Salesforce Architect

Agentforce Architecture

CPQ & Revenue Cloud

Security Architecture

AI Safety & Grounding

Apex & Lightning

APIs & Enterprise Integration

MuleSoft

LLM Context Engineering

Multi-agent Patterns

Tools

MuleSoft

Apex

Salesforce Platform

Job description

Job Summary

We are currently seeking a Salesforce Architect to join our team in Bangalore, Karntaka (IN-KA), India (IN).

Responsibilities

• Own end-to-end solution architecture across Agentforce, Salesforce CPQ and Revenue Cloud Advanced.
• Architect agent-assisted and agentic workflows across opportunity, configuration, pricing, quoting, contracting, ordering and revenue lifecycle processes.
• Design agent orchestration patterns, including tool/function calling, workflow delegation, multi-agent patterns, state management and memory.
• Architect integration of Agentforce with Salesforce automation, Apex, Flow, APIs, MuleSoft and external enterprise services.
• Define appropriate use of LLMs, deterministic logic, workflow engines and traditional automation, rather than defaulting all use cases to generative AI.
• Design context engineering and retrieval strategies, including structured/unstructured grounding, retrieval depth, metadata filtering and relevance optimization.
• Establish secure agent action patterns using least-privilege access, guardrails, validation, approval checkpoints and human-in-the-loop mechanisms.
• Define AI evaluation frameworks covering answer quality, grounding, hallucination, task completion, tool selection, latency and business outcomes.
• Establish observability across agent reasoning paths, actions, integration failures, token/credit consumption and operational performance.
• Assess model and platform trade-offs across quality, latency, context window, cost, privacy and enterprise constraints.
• Architect resilient action layers and transactional integration patterns for revenue processes where consistency and recoverability is critical.
• Advise programs on consumption-based economics, AI credit/token optimization and architectural approaches to control run-time cost.
• Lead architecture reviews, design authorities and technical governance across global delivery teams.
• Mentor technical architects, developers and Agentforce specialists.

Required Technical Expertise

• Salesforce Agentforce and associated agentic architecture concepts.
• Salesforce CPQ and Revenue Cloud Advanced / Revenue Lifecycle Management.
• Salesforce Sales Cloud and core platform architecture.
• Agent orchestration and tool/function calling.
• Multi-agent architectures, delegation and coordination patterns.
• Agent state, short/long-term memory and session/context management.
• MCP and agent-to-agent interoperability concepts/patterns.
• RAG, semantic/vector search, embeddings, chunking and retrieval optimization.
• Context engineering beyond basic prompt engineering.
• Evaluation frameworks and AI observability.
• AI safety, grounding, guardrails and least-privilege action design.
• LLM model selection and architectural trade-offs.
• Classic NLP concepts including intent classification, entity extraction, semantic similarity and ranking.
• Apex, Lightning Platform, Flow, APIs and enterprise integration patterns.
• Strong understanding of asynchronous processing, transaction boundaries, resiliency, retries and idempotency.
• Security architecture including sharing, CRUD/FLS, permission models and data protection.

Preferred Qualifications

• 15+ years overall technology experience; 10+ years in Salesforce CPQ / Revenue Cloud architecture.
• Proven experience architecting enterprise CPQ / Quote-to-Cash implementations.
• Salesforce Application/System/Technical Architect credentials strongly preferred.
• Agentforce and Revenue Cloud-related certifications or demonstrable implementation experience.
• Experience with MuleSoft and large enterprise integration landscapes preferred.
• Ability to communicate architectural decisions to both engineering teams and senior business stakeholders.