Custom AI

Deloitte is seeking a Full Stack CRM Architect to own the design and delivery of components of custom, AI-augmented Customer Relationship Management platforms. This role sits between hands-on engineering and solution architecture: you will lead module- and feature-level design decisions, build critical parts of the platform yourself, and provide day-to-day technical direction to a small delivery pod.

You will partner closely with Managers and Senior Managers/Architects to translate the engagement's overall architectural vision into working software, while mentoring Consultants and helping instill Deloitte's engineering standards on the ground. This is a strong next step for engineers ready to move from building features to owning the design of the systems those features live in.

1. Architecture & Solution Design (Module Ownership)

•     Own the detailed design of specific modules or services within custom CRM platforms — including data models, API contracts, and front-end structures — in line with the overall architecture set by the Manager/Architect. May approve module-level design changes independently; changes affecting the overall architecture pattern require Architect/Manager sign-off.

•     Architect and build full-stack features using modern frameworks (React, Angular, Next.js) for frontend and Node.js or Python/FastAPI for backend, with an eye toward scalability and maintainability.

•     Apply and reinforce architecture governance standards and reusable microservice patterns within your workstream; identify where existing patterns should be extended.

•     Contribute technical analysis to build vs. buy decisions, including prototyping and comparative evaluation of candidate approaches.

2. Product & Delivery Leadership

•     Co-lead discovery sprints and user feedback sessions for your workstream; translate business pain points into well-formed backlog items and acceptance criteria.

•     Track adoption and business-outcome metrics for the features your pod delivers, not just delivery dates.

•     Help run innovation labs and internal hackathons, guiding Consultants through prototyping emerging CRM capabilities (AI agents, voice interfaces, personalization engines).

•     Build and help publish reusable components toward Deloitte's proprietary CRM accelerators and reference architectures.

•     Research emerging technologies (agentic frameworks, LLM orchestration tools, edge inference) and recommend where they apply to current engagements.

3. AI, GenAI & Agentic Integration

•     Design and build AI/GenAI features within CRM workflows — including lead-scoring models, predictive components, agentic workflow steps, and intelligent content generation.

•     Build RAG pipelines and LLM orchestration components (LangChain, LlamaIndex) grounded in CRM knowledge bases; implement semantic caching and query routing to reduce inference costs.

•     Apply AI cost-governance practices within your workstream: model cascading (routing simple queries to smaller models), token budget tracking, and prompt compression.

•     Deploy and tune inference-serving components (containerized vLLM, managed inference endpoints), applying batching and caching strategies under senior guidance.

•     Build conversational AI features (chatbots, virtual agents) that automate Tier-1 service cases, meeting latency SLAs (<500ms P95) via request batching and streaming.

•     Implement output-validation and hallucination-detection checks for GenAI features you own, escalating drift or quality concerns to the Architect/Manager.

•     Track AI-attributed metrics (pipeline velocity contribution, cost-per-interaction, model efficiency) for your workstream and feed them into program-level reporting.

4. AI Implementation Imperatives — Applied at the Workstream Level

Area

What this level does

Data First

Implement data-quality pipelines and CRM hygiene checks (deduplication, completeness scoring, freshness SLAs) for your module ahead of any AI deployment.

Scalability by Design

Design your module's AI-serving components to scale horizontally from day one (autoscaling, async queues) in line with the program's overall pattern.

Cost Efficiency

Right-size models to task complexity within your workstream; implement semantic caching and monitor token spend against budget for the features you own.

Adaptable Architecture

Design your module with modular prompt layers, pluggable model backends, and configurable workflow steps so it can evolve without rework.

Change & Adoption

Build intuitive UX and instrument engagement metrics for your features; surface adoption friction to the Manager/Architect and feed it into the roadmap.

Ethical AI

Implement bias-detection and fairness checks for predictive models in your workstream; flag issues to the engagement's model-governance cadence.

5. Integration

•     Design and build integrations with legacy systems, ERPs (SAP, Oracle, Microsoft Dynamics), MDM platforms, and third-party tools using REST, SOAP, GraphQL, and event-driven architectures (Kafka, RabbitMQ).

•     Lead integration of your workstream's CRM components with marketing automation platforms, communication APIs (Email, SMS, WhatsApp), and data lake/warehouse environments (Snowflake, Databricks).

6. Database Architecture & Performance

•     Design relational and non-relational data models for your module, optimized for high-volume customer interaction data; apply indexing, partitioning, and materialized views for query performance.

•     Lead performance-engineering tasks within your workstream: query plan analysis, connection pooling, read-replica routing, and cache-aside patterns (Redis/Memcached).

•     Apply SQL (PostgreSQL, SQL Server) and NoSQL (MongoDB, Cassandra) technologies, choosing polyglot persistence approaches where appropriate.

7. Security, Compliance & Cloud Engineering

•     Ensure your workstream's solutions adhere to data-privacy regulations (GDPR, CCPA, HIPAA) and enterprise security standards (RBAC, OAuth2/SAML, field-level encryption, audit logging).

•     Design and deploy containerized, cloud-native services on AWS, Azure, or GCP using Docker and Kubernetes; build and maintain GitOps-based CI/CD pipelines aligned with DevSecOps practices.

8. Delivery Excellence

•     Provide day-to-day technical oversight and code-quality assurance for your pod; run architecture and code reviews and help maintain the technical-debt register.

•     Support complex migration and modernization workstreams, defining measurable success criteria for your piece of the program.

•     Proactively identify technical risks and dependencies within your workstream and escalate mitigation options to the Manager/Architect.

9. Practice & Team Development

•     Contribute to Deloitte's Custom CRM practice by building internal accelerators, code libraries, and architectural playbooks.

•     Co-author point-of-view content, white papers, and client-ready materials on AI-driven CRM topics, in partnership with senior architects.

•     Mentor 1–3 Consultants: pair on design and code reviews, and help develop their engineering and CRM domain skills.

•     Represent your workstream in client working sessions, providing technical clarity on progress, trade-offs, and risks.

•     6-9 years of experience in software development and application engineering, including meaningful exposure to CRM system design or customer data platforms.

•     4+ years of hands-on full-stack development using modern web frameworks (React, Angular, Vue) and backends (Node.js, Python, Java).

•     Solid understanding of CRM domain concepts — Leads, Opportunities, Account Management, Sales Pipelines, Service Cases — including building custom fields, workflows, and automation logic.

•     Working knowledge of AI/ML integration within CRM contexts: predictive lead scoring, churn modeling, recommendation engines, and conversational AI.

•     Hands-on experience with GenAI frameworks (LangChain, LlamaIndex) and LLM integration patterns (RAG, function calling, semantic caching, prompt optimization).

•     Experience with relational (PostgreSQL, SQL Server) and NoSQL (MongoDB, Cassandra) database design and performance tuning.

•     Experience integrating CRMs with ERPs, marketing automation tools, or communication platforms via REST, SOAP, GraphQL, or event-driven patterns.

•     Experience deploying cloud-native solutions on AWS, Azure, or GCP using Docker/Kubernetes and CI/CD pipelines.

•     Working understanding of enterprise security and compliance (GDPR, CCPA, HIPAA) and authentication protocols (OAuth2, SAML, RBAC).

•     Experience contributing to enterprise-scale delivery programs, including participation in client working sessions, with the ability to independently manage day-to-day stakeholder communication within their workstream.

•     Demonstrated ability to mentor junior engineers and lead by example on code quality and design.

•     Experience contributing to programs of approximately $1M-$5M in scope, or equivalent module/workstream level ownership.

•     Applied experience with AI inference optimization: model quantization, batching strategies, or token budget management.

•     Familiarity with LLMOps practices: model versioning, drift monitoring, or cost-performance observability.

•     Experience with headless CRM architectures or extending open-source CRM cores programmatically.

•     Active or in-progress certifications: AWS/Azure Solutions Architect Associate, GCP Professional Cloud Architect, or Salesforce Certified System Architect.

•     Prior exposure to Life Sciences, Healthcare, or other regulated-industry CRM implementations.

•     Prior consulting experience at a Big 4 or Tier 1 systems integrator.

•     Portfolio or demonstrable examples of features or modules built from scratch, with documented performance or cost outcomes.

•     Bachelor's or advanced degree in Computer Science, Information Systems, or a related field.

Competency

Description

Strategic Thinking

Connects module-level design decisions to the engagement's business outcomes; explains the reasoning behind design choices.

Product Mindset

Treats their workstream as a product: defines a mini-roadmap, tracks adoption/outcome metrics, and ships iteratively.

Innovation Drive

Prototypes emerging techniques and helps turn proof-of-concepts into reusable components for the wider practice.

AI & GenAI Fluency

Hands-on command of RAG pipeline design, inference optimization, and responsible-AI guardrails at the module level.

Technical Excellence

Writes clean, scalable code and designs secure, performant components; upholds engineering quality across the workstream.

Architecture Governance

Applies and reinforces established design standards; flags where patterns need to evolve to the Architect/Manager.

Client Centricity

Translates ambiguous requirements into precise technical specifications for their module; balances user needs with delivery constraints.

Stakeholder Communication

Engages client working-level stakeholders with clarity; makes technical trade-offs understandable to non-technical audiences.

People Development

Mentors Consultants through pairing, code reviews, and design discussions; fosters curiosity and rigor within the pod.

Deloitte Consulting's Technology & Digital Transformation practice is a trusted advisor to the world's leading enterprises. As a Full Stack CRM Architect, you will own meaningful pieces of AI-native customer engagement platforms — working alongside world-class engineers, architects, and clients who are redefining how technology creates commercial advantage.

At Deloitte, we believe that together makes progress. You will build components that outlast engagements, develop the mentoring and design skills that prepare you for architecture leadership, and grow within a practice where innovation is a daily discipline, not a quarterly theme.

Deloitte is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status.

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