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Tier-1 brand, mid-level generalist role, and likely metro location increase candidate competition.
Requires combined Salesforce platform and applied GenAI expertise, limiting cross-industry transferability.
Multiple explicit years and mandatory GenAI plus Salesforce skills make shortlisting highly strict.
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Develop and enhance full-stack AI-driven products incorporating GenAI and agentic capabilities, ensuring high-quality, lean engineering solutions that deliver measurable customer and business outcomes.
Lead technical efforts across requirement analysis, design, development, testing, integration, and maintenance, while managing cost and quality KPIs throughout the software development lifecycle.
Collaborate cross-functionally with product teams, customers, and engineering peers to align solutions with business goals and deliver iterative, cost-aware, and scalable deployments using modern software engineering and AI practices.
Bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline.
Minimum 5 years’ experience with Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks.
Minimum 3 years’ experience developing AI/ML and agentic applications, including GenAI with LLM integration (OpenAI, Anthropic, or open source), RAG pipelines, prompt engineering, and vector databases.
Minimum 5 years’ experience with Salesforce technologies including Apex, Visualforce, Lightning Components, JavaScript, SOQL, Salesforce AppExchange, and cloud-native engineering on Salesforce platform services; plus working knowledge of Salesforce CI/CD tools like Salesforce DX, GitHub, and SonarQube.
Experienced in building and deploying AI/ML-powered, scalable SaaS products with strong applied AI and Salesforce PaaS expertise, including GenAI and agentic AI frameworks.
Demonstrates ownership for end-to-end product delivery, balancing customer value, engineering cost, code quality, and iterative release using modern DevSecOps and SSDLC practices.
Operates effectively within Agile, Lean, or SAFe environments and engages cross-functional teams to translate business needs into robust technical solutions consistently aligned with strategic outcomes.