Integration Architect (AI & Salesforce)

Position Summary The Integration Architect (AI & Salesforce) will lead the design and implementation of enterprise integration solutions connecting Generative AI, Agentic AI systems, and the Salesforce ecosystem. This role is responsible for architecting scalable, secure, and high-performing AI-driven integrations that align with enterprise architecture standards. The architect will collaborate with business stakeholders, AI engineering teams, Salesforce developers, and infrastructure teams to deliver intelligent automation, advanced analytics, and conversational AI capabilities across the organization. Key Responsibilities Design end-to-end integration architectures connecting GenAI/LLM platforms with enterprise systems and the Salesforce ecosystem Architect and implement Agentic AI systems incorporating planning, reasoning, orchestration, and decision-making components Lead AI-driven integration initiatives leveraging APIs, middleware, microservices, and event-driven architectures Integrate AI models with Salesforce platforms including Agentforce and Salesforce Einstein Design Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration frameworks Ensure secure data exchange, governance, and compliance across integrated systems Collaborate with cloud teams across AWS, Azure, GCP, IBM Cloud, and Salesforce environments Implement best practices for version control, CI/CD, and DevOps integration Provide technical leadership, architectural documentation, and mentorship to development teams Support Agile/Scrum development processes and participate in design reviews Minimum Requirements Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field (or equivalent practical experience) 8–10 years of experience as an Integration Architect in enterprise environments 2+ years of experience designing and deploying GenAI/LLM-powered applications 1+ year of experience building and integrating Agentic AI systems Strong proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, transformers, LangChain, LangGraph, AutoGen, and LlamaIndex Experience with Natural Language Processing (NLP), including text generation, summarization, and semantic understanding Experience with Reinforcement Learning (RL) techniques and agent training Experience working with large datasets and cloud platforms (AWS, Azure, GCP, IBM Cloud, Salesforce) Experience integrating AI models with enterprise IT systems and APIs Strong knowledge of Git and Agile development practices Required experience with either Agentforce or the Salesforce ecosystem Preferred Skills Experience with prompt engineering and LLM fine-tuning Knowledge of knowledge graphs and semantic reasoning frameworks Experience designing multi-agent AI systems and coordination models Familiarity with Explainable AI (XAI) techniques Experience with MLOps pipelines and production model deployment Experience with containerization technologies (Docker, Kubernetes) Experience with Salesforce development tools (Force.com IDE, Apex Data Loader, AutoRABIT) Experience with IVR technologies such as Avaya and Cisco Experience building chatbot and conversational AI platforms Experience working in onshore/offshore collaboration models Experience using GitHub and enterprise collaboration tools