InMobi Advertising
Company:
https://www.linkedin.com/company/inmobiadvertising
Seniority: Mid-Senior level
Industries: Software Development
Job details:
What is the team like? The GTM (Go-To-Market) Engineering team at InMobi builds and scales the systems that power revenue operations and customer engagement. The team owns a comprehensive Salesforce ecosystem—including Sales Cloud, Data Cloud, and Agentforce—along with Experience Cloud (Customer Community), enabling seamless workflows for Sales, Account Management, and Business teams. A key focus area is building intelligent agents and automations using Agentforce, integrated across Salesforce, Slack, and community platforms. These agents drive productivity, automate workflows, and enable real-time, context-aware actions for internal teams and customer-facing use cases. The team also leverages Slack as a collaboration and execution layer, tightly integrated with Salesforce to trigger workflows, surface insights, and enable faster decision-making. On the backend, the team develops and maintains a scalable middleware platform using Apache Camel and Java, powering event-driven integrations and reliable data exchange across systems. The architecture blends CRM, data platforms, agent-based automation, and distributed systems—focusing on extensibility, real-time processing, and high impact business outcomes. This is a high-impact engineering team operating at the intersection of CRM, AI- driven agents, integrations, and modern enterprise platforms.
Skillset: Agentforce (Agent Development), Salesforce (Advanced), Apex, Lightning Web Components (LWC), Experience Cloud, Data Cloud, Slack, CI/CD (Copado/GitHub), Event-Driven Architecture, Integration Patterns (Apache Camel), Java, Automation & Workflow Design, Performance Optimization, Python
Role Overview: As an Architect/Staff Engineer I at InMobi, you will be a mentor, technical leader driving the design, development, and delivery of Agentic AI solutions on Salesforce platform. You will serve as the bridge between our CRM infrastructure and AI-driven product experiences - shaping how InMobi's go-to-market and revenue systems evolve and uplift in an era of autonomous workflows and intelligent automation. You'll work closely with product team, RevOps, Data and product engineering to build scalable, distributed, enterprise-grade solutions that power InMobi's growth.
What you'll do
Salesforce platform engineering:
Design, build, and deploy scalable Salesforce-centric solutions supporting InMobi's revenue and growth operations - including Agentforce / AI-driven orchestration, prompt templating, Data Cloud integration, complex Apex, LWC, and integration layers. Design high-scale integrations with enterprise-grade architectures leveraging Platform Events, Change Data Capture (CDC), and REST/SOAP APIs to enable real-time data flows across the business. Build features enabling seamless integration between Salesforce structured/unstructured data and downstream AI agents for faster insights and decision-making. Deploy and monitor Salesforce-integrated products with an emphasis on agent observability, telemetry, and auditability. Develop best-in-class data health monitoring and context enrichment pipelines to ensure CRM data used by agents is reliable, governed, and audit-ready.
Agentic AI & intelligent automation:
Lead technical solutioning for full-lifecycle projects focused on how Salesforce will power autonomous workflows, co-pilots, and multi-agent systems - contributing to a "data-first, agent-aware" architecture strategy. Partner with product management and business stakeholders to prioritize CRM data products that drive autonomous decision-making, context-rich recommendations, and discoverable data services for next-gen AI agents and LLM-based systems.
Distributed systems & backend:
Architect and scale distributed systems that interact with Salesforce for real-time data synchronization, leveraging Kafka, Spark, or similar streaming technologies. Write clean, testable, and high-performance backend middleware in Java that bridges CRM and cloud services at scale.
Engineering excellence:
Champion DevOps best practices including Salesforce DX, CI/CD pipelines (GitHub Actions), and automated testing frameworks. Mentor engineering teams, set technical standards, and enforce code quality and best practices across squads. Contribute to InMobi's platform reliability with a focus on fault tolerance, performance optimization, and scalability
What you'll bring
- 10+ years of experience in enterprise software development with a focus on scalable, fault-tolerant, CRMintegrated architectures.
- 2–3 years of hands-on experience with Agentforce, Data Cloud, and cloud platforms (GCP or Azure) and their connectivity to Salesforce.
- Deep expertise in Salesforce architecture: Apex, LWC, Salesforce Shield, CRM data modelling, and high-volume data processing patterns.
- Proven experience with advanced Salesforce integrations including Platform Events, CDC, and complex REST/SOAP API integrations.
- Experience writing optimized SOQL/SOSL and managing large datasets within Salesforce multi-tenant environments.
- 2 Experience writing clean, testable backend code in Java or Python for middleware services (Apache Camel, MuleSoft) bridging CRM and external cloud services.
- Mastery of Salesforce DX, CI/CD pipelines (GitHub Actions / Copado), and AI automated testing and deployment frameworks. Knowledge of Salesforce data security including Data Mask, encryption, and governance in the context of agent auditability and compliance.
- Solid understanding of distributed systems and how tools like Kafka or Spark interact with Salesforce for real-time data synchronization.
Preferred qualifications
- Prior experience at ad-tech or high-scale B2B SaaS companies.
- Track record of building and delivering Agentic AI solutions for enterprise systems - including sophisticated Salesforce UIs and high-performance backend services.
- Experience with Salesforce Media Cloud, Order Management System (OMS), Revenue Cloud, or related platforms.
- Familiarity with LLM evaluation, agent observability tooling, or RAG pipeline design.
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