Salesforce Architect

NTT DATA, Inc.; Bengaluru; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

NTT DATA seeks a highly experienced 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 with Salesforce, MuleSoft, APIs and external services.

You will design agent orchestration patterns, define AI usage, ensure security, observability and cost-efficient architectures across revenue lifecycle processes, mentoring architects and delivery teams globally.

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.

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 are 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.

Skills

Salesforce Architect

Agentforce

CPQ & Revenue Cloud

Sales Cloud

Multi-agent architectures

AI/LLM usage

Security by design

Observability

Apex/Lightning

Tools

Apex

Flow

APIs

MuleSoft

LLM usage patterns

Job description

Job Description:

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization.

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

\"Key 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 are 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.\