Agentforce Architect (Remote, KA, IN)

🏢 NTT DATA · all NTT DATA jobs
📍 India
📅 Posted 2026-09-06 · via Himalayas
🏷 Agentforce-Architect,Salesforce-Architect,Solutions-Architect,AI-Solutions-Architect,Technical-Architect,Senior-Remote-Architect,Lead-Salesforce-Architect,Agentforce-Architecture,Remote-Solutions-Architect
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Req ID: 387936

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, apply now.

We are currently seeking a Agentforce Architect to join our team in Remote, 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.

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