Senior Engineer, Systems Engineering
On-sitePune, Maharashtra, India
Pune, Maharashtra, IndiaOn-siteFull TimeSenior LevelBachelors DegreeLarge
Full TimeSenior LevelBachelors DegreeLarge
Job Summary
Design, develop, and deploy AI-powered Salesforce solutions leveraging Agentforce, Einstein AI, and Einstein Copilot to automate complex business workflows. Build custom Apex, Lightning Web Components, and Flows while integrating external LLMs via REST/SOAP APIs. Configure agent topics, actions, and instructions to power generative AI features, and collaborate with data engineers to ensure high-quality Data Cloud pipelines. Conduct code reviews, mentor junior developers, and monitor AI model performance in production environments. Participate in Agile ceremonies and stay ahead of the Salesforce AI roadmap to recommend adoption strategies.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Artificial Intelligence, or a related field (or equivalent work experience)
- 5+ years of hands-on Salesforce development experience
- Proficiency in Apex, Lightning Web Components (LWC), SOQL/SOSL, and Salesforce Flow
- Hands-on experience with Salesforce Einstein AI features (Einstein Prediction Builder, Einstein Classification, Einstein Bots, or Einstein Copilot)
- Experience developing or configuring Agentforce agents, including agent topics, actions, and instructions
- Solid understanding of Prompt Builder and generative AI prompt engineering within the Salesforce platform
- Experience with REST and SOAP API integrations and connecting Salesforce to external AI/ML services
- Familiarity with Salesforce Data Cloud or similar customer data platform (CDP) technologies
- Strong understanding of Salesforce data model, security model, and governor limits
- Experience with Salesforce DX (SFDX), Git, and CI/CD deployment pipelines
- Active Salesforce Certified Platform Developer I, Salesforce Certified AI Associate/ AI Specialist Certification
- Bachelor's degree in computer science, software engineering, computer engineering, information systems, or a related field, or equivalent experience required
- 4+ years of experience in software engineering, systems engineering, application development, platform engineering, or a related field required
Desired Qualifications
- Salesforce Certified Platform Developer II certification
- Salesforce Data Cloud Consultant certification
- Exposure with large language models (LLMs) such as OpenAI GPT, Azure OpenAI, or Anthropic Claude, and integrating them with Salesforce
- Familiarity with vector databases, RAG (Retrieval-Augmented Generation) architectures, or embedding models in enterprise AI contexts
- Understanding of responsible AI principles, including bias detection, explainability, and ethical AI governance
- Experience in the healthcare, pharmaceutical, or life sciences industry
- Familiarity with Salesforce Shield and enterprise-grade data security and compliance practices
- Experience working in large, multi-cloud Salesforce enterprise organizations
- Strong communication skills with the ability to articulate AI concepts to both technical and non-technical audiences
- AWS Certified Cloud Practitioner (CLF-C02), AZ-900: Azure Fundamentals, RHCSA (Red Hat Certified System Administrator) certification, or equivalent preferred
- Knowledge of software and systems engineering principles, development lifecycle practices, testing strategies, and production support models
- Knowledge of system architecture, application design, integration patterns, debugging techniques, version control, and deployment approaches
- Knowledge of performance engineering, reliability, scalability, secure design, and operational resilience concepts
- Skill in coding, configuration, technical design, troubleshooting, root cause analysis, and structured problem solving
- Skill in using development frameworks, testing tools, source control platforms, CI/CD pipelines, collaboration tools, and work management systems
- Ability to lead moderately complex to complex engineering work independently while applying sound judgment, quality standards, and risk awareness
- Ability to collaborate effectively with technical and non-technical stakeholders and communicate solution options, dependencies, risks, and progress clearly
- Knowledge of advanced software and systems engineering principles, development lifecycle practices, testing strategies, and production support models
- Knowledge of application architecture, system design, integration patterns, cloud and infrastructure components, and secure engineering practices
- Knowledge of performance engineering, scalability, reliability, resilience, observability, and operational support frameworks
- Skill in technical design, coding or configuration, debugging, root cause analysis, performance tuning, and structured problem solving
- Skill in using development frameworks, testing tools, source control platforms, CI/CD pipelines, observability tools, collaboration platforms, and work management systems
- Ability to lead complex engineering work independently while applying strong technical judgment, quality standards, and risk awareness
- Ability to influence technical direction, guide design decisions, and collaborate effectively with technical and non-technical stakeholders
- Ability to mentor less experienced engineers and drive adoption of engineering best practices, documentation standards, and continuous improvement methods
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