Custom AI - Software Engineer II - Sales & Service - Customer

Custom AI
Customer | S&S | Consultant
About the Role
Deloitte is seeking a Full Stack CRM Developer to help design, build, and deliver bespoke, AI-augmented Customer Relationship Management applications. This is a hands-on engineering role for someone early in their consulting career who wants to build modern, scalable customer engagement platforms — not configure off-the-shelf tools.
You will work under the guidance of Senior Consultants, Managers, and Architects to build features, integrate AI capabilities, and deliver high-quality, well-tested code across the full stack. This role is designed to build deep technical skills in CRM engineering and GenAI integration while developing the foundation for future architecture and leadership roles at Deloitte.
Key Responsibilities
1. Architecture & Solution Design (Contributor)
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Build components of custom CRM platforms — including data models, API endpoints, microservices, and front-end features — following the architecture patterns and standards set by the engagement's architects.
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Develop full-stack features using modern frameworks (React, Angular, Next.js) for frontend and Node.js or Python/FastAPI for backend, under the direction of senior technical leads.
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Follow established architecture governance standards and reusable microservice patterns; raise opportunities for improvement to senior architects.
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Support build vs. buy evaluations by prototyping and testing candidate approaches as directed.
2. Product & Delivery Mindset
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Participate in discovery sprints and user feedback sessions; help translate business pain points into user stories and backlog items.
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Support a product mindset by helping track adoption and usage metrics for the features you deliver.
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Participate in innovation labs and internal hackathons, prototyping emerging CRM capabilities under guidance from senior team members.
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Contribute code, tests, and documentation to Deloitte's CRM accelerators and reference architectures.
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Stay current on emerging technologies (agentic frameworks, LLM tooling, edge inference) and share relevant findings with the team.
3. AI, GenAI & Agentic Integration
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Build and test AI/GenAI features within CRM workflows — such as lead-scoring models, content generation, and chatbot integrations — as specified by the architecture team.
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Support development of RAG pipelines and LLM orchestration components (LangChain, LlamaIndex) under senior guidance.
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Implement token-usage tracking and basic semantic caching per the engagement's established cost governance framework.
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Assist with deploying and testing inference-serving components, including containerized vLLM or managed inference endpoints.
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Build and test conversational AI features (chatbots, virtual agents), validating functionality against defined latency SLAs (e.g., <500ms P95).
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Support output-validation and hallucination-detection testing as part of GenAI QA processes.
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Help capture basic AI usage metrics (cost-per-interaction, latency, accuracy) for reporting to senior team members.
4. AI Implementation Fundamentals
Area
What this level does
Data First
Execute data-quality checks and CRM hygiene tasks (deduplication, completeness scoring) as defined by the team's data standards, before AI features are deployed.
Scalability by Design
Build components following the team's established autoscaling and async-queue patterns rather than introducing one-off solutions.
Cost Efficiency
Apply caching and token-budget practices defined by the engagement; monitor and report token spend for the features you own.
Adaptable Architecture
Build modular, configurable components (prompt layers, pluggable services) rather than hard-coded logic, per team design guidance.
Change & Adoption
Build intuitive UX per design specifications and help instrument usage/engagement metrics; surface adoption friction observed during testing.
Ethical AI
Apply bias-detection and fairness-testing checklists provided by senior architects when validating model outputs.
5. Integration Support
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Build integrations with legacy systems, ERPs, MDM platforms, and third-party tools using REST, SOAP, GraphQL, and event-driven patterns (Kafka, RabbitMQ), following designs provided by senior architects.
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Support integration of the CRM with marketing automation platforms, communication APIs (Email, SMS, WhatsApp), and data lake/warehouse environments (Snowflake, Databricks).
6. Database Development & Performance
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Build and maintain relational and non-relational data models per designs provided by senior architects; implement indexing and partitioning as specified.
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Support performance-tuning tasks: query optimization, connection pooling, and cache implementation using Redis/Memcached.
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Write and maintain SQL/NoSQL code across PostgreSQL, SQL Server, MongoDB, and Cassandra environments.
7. Security, Compliance & Cloud Engineering
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Implement security controls (RBAC, OAuth2/SAML, field-level encryption, audit logging) in line with compliance requirements (GDPR, CCPA, HIPAA).
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Build and deploy containerized services on AWS, Azure, or GCP using Docker and Kubernetes; contribute to CI/CD pipelines.
8. Delivery Excellence
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Deliver high-quality, well-tested code that adheres to team coding standards; participate actively in code reviews.
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Support migration and modernization workstreams under senior direction.
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Flag technical risks, blockers, and dependencies to project leads in a timely manner.
9. Practice & Community Contribution
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Contribute to internal accelerators, code libraries, and technical documentation.
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Support the creation of point-of-view content and client-ready materials under the guidance of senior team members.
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Participate in Deloitte's technical communities of practice and knowledge-sharing sessions.
Required Qualifications
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3-6 years of experience in software development, with exposure to CRM system design or customer data platforms a plus.
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2+ years of hands-on full-stack development using modern web frameworks (React, Angular, or Vue) and backends (Node.js, Python, or Java).
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Working knowledge of CRM domain concepts — Leads, Opportunities, Account Management, Sales Pipelines, Service Cases.
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Foundational understanding of AI/ML concepts as applied to CRM (lead scoring, recommendation logic, conversational AI).
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Exposure to GenAI frameworks (LangChain, LlamaIndex) or LLM integration patterns (RAG, function calling) through coursework, personal projects, or prior engagements.
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Familiarity with relational (PostgreSQL, SQL Server) and NoSQL (MongoDB, Cassandra) databases.
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Experience integrating applications via REST, SOAP, or GraphQL APIs.
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Exposure to cloud-native deployment (AWS, Azure, or GCP) using Docker/Kubernetes.
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Basic understanding of security and compliance concepts (OAuth2, SAML, RBAC, GDPR/CCPA/HIPAA).
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Strong communication skills and the ability to work effectively within cross-functional delivery teams.
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Experience contributing to a delivery POD or project team of roughly 3-6 engineers or equivalent team-based project work.
Preferred Qualifications
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Personal, academic, or hackathon projects involving LLM integration, RAG, or agentic frameworks.
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Familiarity with infrastructure-as-code (Terraform, Pulumi).
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Cloud certifications at the Associate level (AWS, Azure, or GCP).
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Bachelor's degree in Computer Science, Information Systems, or a related field.
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Prior internship, co-op, or project experience in a consulting or client-facing environment.
Core Competencies
Competency
Description
Strategic Thinking
Understands how assigned tasks connect to broader business outcomes; asks clarifying questions to align work with client goals.
Product Mindset
Understands the product being built; contributes input on backlog items and incorporates user feedback into delivered work.
Innovation Drive
Curious about emerging technologies; experiments in labs/hackathons and shares findings with the team.
AI & GenAI Fluency
Builds and tests AI/GenAI features under guidance; developing foundational RAG and LLM integration skills.
Technical Excellence
Writes clean, tested, well-documented code; follows engineering best practices and team coding standards.
Architecture Awareness
Follows established architecture standards and design principles; escalates gaps or inconsistencies to senior architects.
Client Centricity
Translates specific requirements into working code; asks questions to clarify ambiguity before building.
Communication
Communicates clearly with team leads and peers; developing confidence presenting work to internal stakeholders.
Growth Mindset
Actively seeks feedback and mentorship; supports peers through pairing, reviews, and knowledge sharing.
Why Deloitte?
Deloitte Consulting's Technology & Digital Transformation practice is a trusted advisor to the world's leading enterprises. As a Full Stack CRM Developer, you will build the technical foundation of your consulting career — working alongside world-class engineers and architects on real, high-impact AI-native CRM platforms.
At Deloitte, we believe that together makes progress. You will build products that outlast engagements, learn from experienced architects and managers, and grow within a practice where curiosity and continuous learning are part of the daily discipline.
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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