Join NTT DATA as a Salesforce Architect and contribute to innovative, adaptable, and forward-thinking projects. This role offers the opportunity to shape end-to-end solution architectures and drive advancements in agent-assisted and agentic workflows.

Focus on designing complex agent orchestration patterns and seamlessly integrating Agentforce with core Salesforce technologies, including Apex, Flow, APIs, and MuleSoft. You'll define the strategic use of AI models, ensuring a balanced approach between generative and deterministic logic for optimal solutions.

This position involves architecting robust context engineering and retrieval strategies, alongside establishing secure agent action patterns and comprehensive AI evaluation frameworks. You will be instrumental in defining observability across agent reasoning and operational performance, while assessing model and platform trade-offs for enterprise constraints.

Lead architecture reviews, guide technical governance, and mentor a team of technical architects, developers, and specialists. This role is key to advancing our capabilities in AI and digital infrastructure.

Develop and own comprehensive solution architectures across Agentforce, Salesforce CPQ, and Revenue Cloud.

Design agent-assisted and agentic workflows for the entire lifecycle of opportunities, quoting, contracting, ordering, and revenue processes.

Architect advanced agent orchestration patterns, including tool/function calling, workflow delegation, multi-agent collaboration, state management, and memory.

Seamlessly integrate Agentforce with Salesforce automation, Apex, Flow, APIs, MuleSoft, and external enterprise services.

Define the appropriate application of LLMs, deterministic logic, and workflow engines, rather than relying solely on generative AI.

Design sophisticated context engineering and retrieval strategies, encompassing grounding, retrieval depth, metadata filtering, and relevance optimization.

Establish secure agent action patterns employing least-privilege access, guardrails, validation, approval checkpoints, and human-in-the-loop mechanisms.

Define AI evaluation frameworks to assess answer quality, grounding, hallucination, task completion, tool selection, latency, and business outcomes.

Implement observability across agent reasoning paths, actions, integration failures, token consumption, and operational performance.

Assess model and platform trade-offs considering quality, latency, context window, cost, privacy, and enterprise constraints.

Architect resilient action layers and transactional integration patterns for critical revenue processes.

Advise programs on consumption-based economics, AI cost optimization, and architectural approaches to manage run-time expenses.

Lead architecture reviews, design authorities, and technical governance across global delivery teams.

Mentor technical architects, developers, and Agentforce specialists.

Possess expertise in Salesforce Agentforce and associated agentic architecture concepts.

Demonstrate deep knowledge of Salesforce CPQ, Revenue Cloud Advanced, and Revenue Lifecycle Management.

Exhibit strong understanding of Salesforce Sales Cloud and core platform architecture.

Proficiency in agent orchestration and tool/function calling is essential.

Familiarity with multi-agent architectures, delegation, and coordination patterns.

Experience with agent state, short/long-term memory, and session/context management.

Understanding of MCP and agent-to-agent interoperability concepts and patterns.

Proficiency in RAG, semantic/vector search, embeddings, chunking, and retrieval optimization.

Experience with context engineering beyond basic prompt engineering.

Knowledge of evaluation frameworks and AI observability.

Familiarity with AI safety, grounding, guardrails, and least-privilege action design.

Experience in LLM model selection and architectural trade-offs.

Solid grasp of classic NLP concepts, including intent classification, entity extraction, semantic similarity, and ranking.

Proficiency in Apex, Lightning Platform, Flow, APIs, and enterprise integration patterns.

Strong understanding of asynchronous processing, transaction boundaries, resiliency, retries, and idempotency.

Knowledge of security architecture, including sharing, CRUD/FLS, permission models, and data protection.

Preferred qualifications include 15+ years of overall technology experience, with at least 10 years in Salesforce CPQ / Revenue Cloud architecture. Proven experience architecting enterprise CPQ / Quote-to-Cash implementations is highly valued. Salesforce Application/System/Technical Architect credentials, Agentforce and Revenue Cloud-related certifications or demonstrable experience, and experience with MuleSoft are strongly preferred. The ability to articulate architectural decisions to both engineering teams and senior business stakeholders is crucial.