Activation Solution Engineer- TMT/CBS

Role

An Activation Solution Engineer on the Activation Solution Engineering team will provide technical architecture, leadership, and delivery ownership for Agentforce (Salesforce’s intelligent agent) implementations. The role involves designing and deploying enterprise-grade AI agents and autonomous workflows, defining reusable architecture and guardrails, and driving integrations across Salesforce clouds and external systems.

Key Responsibilities

• Contribute to architecture, implementation, and deployment of scalable, reliable, and compliant Agentforce solutions.
• Design intelligent agents and supporting components leveraging LLMs, prompt engineering, integration technologies, and orchestration frameworks.
• Define reusable patterns for agent skills, guardrails, and multi-agent collaboration.
• Drive integrations across Salesforce product clouds (e.g., Service Cloud, Field Service) and external systems.
• Contribute to observability, performance optimization, monitoring, and telemetry frameworks.
• Build reusable accelerators, deployment frameworks, and reference architectures.
• Mentor and coach newer solution engineers and architects on Agentforce capabilities.
• Partner with Product Owners, Architects, Customer Success, and Partners on pilots, innovation programs, and delivery plans.
• Define AI governance, guardrail frameworks, and DevOps/CI-CD/release standards; ensure compliance with Responsible AI and data security policies.

Requirements (Minimum Qualifications)

• 5+ years of relevant professional experience in a technical pre-sales or consulting role, with a focus on enterprise architecture.
• Experience with Salesforce D360 (formerly Data Cloud).
• Deep experience with Salesforce Service Cloud and Field Service Lightning implementations.
• Experience designing, developing, and maintaining RESTful services.
• Knowledge of modern AI concepts including LLMs, prompt and context engineering, human-in-the-loop, fine-tuning, RAG architectures, and multi-agent patterns.
• Experience integrating LLMs and AI services into enterprise applications.
• Experience with public cloud infrastructure (AWS/Azure/GCP).
• Understanding of distributed systems, security concepts (mTLS, PKI, OAuth/SAML), and observability/performance practices.
• Demonstrated ability to learn new technologies quickly and work in customer-facing technical roles.

Preferred Qualifications

• Hands-on experience with Agentforce, conversational AI, or intelligent agents.
• Salesforce platform architecture expertise and relevant Salesforce Architect or Consultant certifications.
• Familiarity with CI/CD, test-driven development, automated testing, and DevOps best practices.
• Knowledge of integration architectures and APIs (e.g., AWS API Gateway, MuleSoft).
• Experience with Java, Python, JavaScript/Node, Scala, or Go.
• Experience with NoSQL/datastore technologies (Cassandra, HBase, Elasticsearch) and distributed caching/load balancing.
• Experience with open source projects and community contributions; multi-agent deployments and autonomous workflows.

Compensation

• Typical base salary range for this position: $134,750 - $244,510 annually (base only).
• Different range for certain locations (California, New York and select metropolitan areas): $148,190 - $269,080 annually.

Benefits

• Time off programs
• Medical, dental, and vision insurance
• Mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program