below marketmost similar roles pay hereabove market
This role pays more than
51%
of similar roles. Most pay
$186,800–$254,750
— the blue band above.
At the midpoint, this role pays about
$216k
versus about
$221k
for comparable roles.
Based on 240 similar postings.
Employer
About Salesforce
Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing
Salesforce currently has
221 open roles
on FindRole.
Listed pay typically runs
$148,500–$260,100
across 125 roles with salary data.
The Senior Engineering Manager, AgentExchange Go To Market App leads the software engineering team responsible for transforming the AppExchange into a fully integrated, transactable marketplace. This role involves leading architecture discussions, defining technical strategy, and mentoring developers to build a streamlined, scalable purchasing and billing experience. The objective is to accelerate ISV sales and recover lost revenue by enabling partners to sell and customers to purchase, deploy, and pay for solutions without manual intervention. Key responsibilities include resolving systemic issues, coordinating with product owners, and ensuring long-term stability. The position requires expertise in Java/JVM languages, modern cloud architecture, Kubernetes, and Infrastructure-as-Code using Terraform. Candidates must demonstrate proficiency in AWS, Azure, or GCP while building reliable, self-healing services with robust automation and end-to-end service ownership.
What does a Engineering Manager earn in California?
Median $279400 from 84 postings across 24 companies.
Lead architecture discussions and technical strategy to ensure long-term product stability and scalability.
Resolve systemic technical issues and make data-driven decisions for the AppExchange Go To Market App.
Partner with Product Owners and cross-functional stakeholders to align engineering with product priorities.
Mentor engineering talent by providing technical guidance, career development, and active hiring participation.
Perform hands-on technical work to support the team and maintain personal technical proficiency.
Coordinate delivery schedules and communicate execution risks to relevant stakeholders.
Oversee the development of scalable, highly available services using Java and modern cloud architecture.
What we're looking for
You must have 10+ years of progressive engineering experience.
You must have 3+ years of experience directly managing and mentoring high-performing software engineering teams.
You must have a deep technical background in scalable, highly available platform development with a focus on Java/JVM languages and modern cloud architecture.
You must have experience leading teams or performing hands-on work with AWS, Azure, or GCP, Kubernetes, and Terraform.
You must have a proven track record building reliable, self-healing services with robust automation and end-to-end service ownership.
You should have experience leading complex programs and managing cross-functional stakeholders in a highly matrixed organization (preferred).
You should have driven strategy around and actively used open-source technologies (preferred).
You should have a strong foundation in Agile/Scrum methodologies, secure coding practices, and code quality (preferred).
Agentic AI
Large Language Models
Retrieval-Augmented Generation (RAG)
Reinforcement Learning
RLHF
RLAIF
Natural Language Processing
Distributed Systems
Machine Learning
Model Alignment
Chain-of-Thought
Orchestration Frameworks
Evaluation Frameworks
Observability Systems
Continuous Learning Pipelines
Agentic AI
Large Language Models
Retrieval-Augmented Generation (RAG)
Natural Language Processing
Machine Learning
Reinforcement Learning
RLHF
RLAIF
Distributed Systems
Model Alignment
Chain-of-Thought
Orchestration Frameworks
Evaluation Frameworks
Observability Systems
Continuous Learning Pipelines
Private Cloud Compute
Agentic AI
Large Language Models
Retrieval-Augmented Generation (RAG)
Reinforcement Learning
Natural Language Processing
Distributed Systems
Machine Learning
Chain-of-Thought
Model Alignment
RLHF
RLAIF
Orchestration Frameworks
Evaluation Frameworks
Observability Systems
Continuous Learning Pipelines
On-device Intelligence
Agentic AI
Large Language Models
Retrieval-Augmented Generation (RAG)
Natural Language Processing
Machine Learning
Reinforcement Learning
RLHF
RLAIF
Distributed Systems
Model Alignment
Chain-of-Thought
Orchestration Frameworks
Evaluation Frameworks
Observability Systems
Continuous Learning Pipelines