AI Transformation Consultant / AI Solutions Architect (Agentic AI, Custom CRM, SaaS Platform, Revenue Operations)

Position Overview

We are seeking a highly capable AI Transformation Consultant with strong developer and solutions architecture depth to help design, guide, and support the buildout of a next-generation AI-powered SaaS platform.

This platform is intended to unify the power of a custom CRM, marketing automation, sales enablement, customer service, product management, revenue operations, accounting workflows, data infrastructure, and data warehouse environments into a single intelligent operating system for modern businesses.

At the center of the platform is an agentic AI layer modeled after real corporate structure and decision flows. The vision includes AI agents functioning as role-based digital counterparts across the organization, such as:

• CEO Agent
• CMO Agent
• CFO Agent
• COO Agent
• CSO / Sales Leader Agent
• Service Agent
• Website Agent
• Social Media Agent
• Sales Associate Agent
• Product / Project Agent
• Analytics / Revenue Agent

This role is ideal for someone who can operate at the intersection of AI strategy, applied architecture, platform development, orchestration, integration, and business transformation.

What We Are Building

We are building an AI-native business operating platform that combines:

• Custom CRM capabilities
• Marketing, sales, and service tools
• Customer lifecycle and business lifecycle workflows
• Revenue and operational intelligence
• Data consolidation and warehouse architecture
• Agent-based automation and decision support
• Multi-company / multi-tenant SaaS deployment potential
• AI-driven execution across websites, content, reporting, workflows, and customer interactions

The right candidate should understand not just how to build features, but how to help shape an AI-first architecture that can scale across businesses, departments, users, and use cases.

Core ResponsibilitiesPlatform Strategy & Architecture

• Help define and guide the architecture of an AI-powered SaaS platform integrating CRM, RevOps, MarTech, Service, Product, Finance, and Data environments
• Translate business vision into scalable technical frameworks, product structure, and phased execution plans
• Design system architecture for multi-tenant deployment, role-based access, orchestration, security, observability, and extensibility
• Advise on build-vs-buy decisions, infrastructure choices, model selection, orchestration layers, and long-term platform defensibility

Agentic AI Design

• Design and implement an agentic AI framework that mirrors real business functions and corporate hierarchy
• Architect role-based AI agents with memory, context boundaries, permissions, tool access, escalation logic, and cross-agent collaboration
• Help define how agents coordinate across departments such as sales, marketing, operations, finance, service, and executive oversight
• Guide the development of systems for reasoning, routing, task execution, approvals, auditability, and human-in-the-loop controls

AI / LLM Engineering Guidance

• Evaluate and apply modern model ecosystems including open-source and commercial LLMs
• Design practical workflows using technologies such as LangGraph, Llama, Docker, vector search, retrieval pipelines, prompt frameworks, orchestration tools, and API-connected services
• Advise on model selection, agent memory, embeddings, tool calling, structured outputs, RAG patterns, and production AI workflows
• Support experimentation across platforms including Nemotron, OpenCLA / Claude-family models, Llama-based stacks, and other relevant model ecosystems

CRM + Business Systems Integration

• Guide the integration of the AI layer into a custom CRM and surrounding business systems
• Design workflows spanning:
• lead capture
• sales pipelines
• marketing campaigns
• service operations
• account management
• product/project workflows
• financial and revenue visibility
• reporting and data movement
• Ensure interoperability across APIs, databases, front-end tools, and third-party platforms

Data & Intelligence Layer

• Advise on the design of data pipelines, unified data models, warehouse structures, and operational analytics layers
• Support architecture for customer data, transactional data, marketing data, sales activity, service logs, and financial / operational reporting
• Help shape an environment where AI agents can act on clean, governed, permission-aware business data

Development & Technical Leadership

• Contribute hands-on where appropriate while also providing senior-level guidance to internal or external developers
• Establish engineering standards, modular architecture patterns, deployment discipline, testing approaches, and technical documentation
• Collaborate across product, growth, operations, and executive stakeholders to ensure the system is commercially viable and technically sound

Required ExperienceTechnical / Platform Experience

• Proven experience designing or developing AI-enabled platforms, SaaS products, or custom business systems
• Strong experience with LLM application development, agentic workflows, and AI orchestration frameworks
• Experience with tools and ecosystems such as:
• LangGraph
• Llama
• Docker
• vector databases
• RAG pipelines
• API orchestration
• workflow automation frameworks
• cloud deployment environments
• Familiarity with multiple model providers or model families, including:
• Nemotron
• Claude / similar closed models
• Open-source LLM ecosystems
• Llama variants
• other relevant enterprise or open-weight model environments

Architecture & Systems Thinking

• Experience designing integrated systems across CRM, marketing, sales, customer service, finance, and analytics functions
• Strong understanding of:
• system design
• data architecture
• SaaS platform patterns
• multi-tenant environments
• security and access control
• workflow orchestration
• agent permissions and governance
• Ability to design for scale, maintainability, and real-world business operations rather than just demos or prototypes

Business Transformation Depth

• Experience helping companies modernize workflows through automation, data unification, AI enablement, or platform consolidation
• Strong understanding of how businesses actually operate across departments and handoffs
• Ability to connect technical decisions to business outcomes such as:
• efficiency
• revenue growth
• lower software/tool sprawl
• higher visibility
• better customer lifecycle management
• reduced manual work

Preferred Qualifications

• Experience building or advising on custom CRM systems
• Experience with MarTech, SalesTech, RevOps, Service platforms, or ERP/accounting-adjacent systems
• Experience with containerization, microservices, cloud infrastructure, and deployment pipelines
• Familiarity with data warehouses, ELT/ETL pipelines, BI environments, and semantic business data layers
• Experience designing AI systems with:
• memory strategies
• role-based tool calling
• human approvals
• audit trails
• observability
• fallback logic
• Experience in startup, product-build, or digital transformation environments where ambiguous vision had to become real architecture

Ideal Candidate Profile

The ideal candidate is not just an AI enthusiast or prompt engineer. They are a builder-strategist who understands that real enterprise value comes from combining:

• architecture discipline
• business process design
• scalable engineering
• system integration
• AI orchestration
• product thinking
• commercial practicality

They should be capable of discussing both agent memory design and revenue operations workflow, both Dockerized deployment strategy and customer lifecycle intelligence, both LLM selection tradeoffs and platform monetization logic.

Key Outcomes for This Role

This person will help us:

• define the right architecture for an AI-native SaaS platform
• avoid expensive technical dead ends
• build a credible agentic AI framework that mirrors business structure
• integrate AI deeply into CRM and surrounding business systems
• reduce dependency on fragmented tools by creating a more unified platform
• position the company to scale this as a commercial SaaS offering

Example Areas of Ownership

• AI orchestration architecture
• CRM + workflow integration strategy
• agent role design and task routing
• LLM / model ecosystem evaluation
• structured data and warehouse integration
• internal platform roadmap guidance
• technical vendor/tool assessment
• proof-of-concept to production transition

Nice-to-Have Stack Exposure

Experience with some combination of the following is highly valued:

• Nemotron
• Claude / OpenCLA-type ecosystems
• Llama
• LangGraph
• Docker
• Python
• Node.js
• API-first architectures
• vector databases
• RAG frameworks
• orchestration tools
• workflow engines
• Kubernetes
• Postgres
• Redis
• cloud environments such as AWS, Azure, or GCP
• analytics / warehouse tools
• CRM architecture
• automation platforms

Engagement Type

Consulting / Contract / Fractional / Project-Based

Potential to expand into longer-term architecture leadership depending on fit and contribution.

How to Stand Out

Candidates should be able to demonstrate one or more of the following:

• platforms they helped architect or build
• AI agent systems deployed beyond proof-of-concept
• custom CRM or business system integration experience
• SaaS product experience with real users and business workflows
• examples of turning fragmented operations into unified systems