Greater Noida, Uttar Pradesh
Job Summary
Job Summary: Seeking a highly experienced Salesforce Architect/Lead Developer with 12+ years of expertise in enterprise Salesforce implementations, AI/ML solutions, and custom application development. The ideal candidate should have strong hands-on experience in Generative AI, LLMs, Prompt Engineering, RAG, Agentforce, Python, and AI/ML engineering, along with deep knowledge of Salesforce architecture and integrations. The role requires designing and delivering scalable, secure, AI-powered enterprise solutions leveraging cloud platforms, DevOps practices, MLOps/LLMOps, and modern software engineering methodologies. Key Responsibilities: 12+ years of hands-on Salesforce development experience with enterprise-scale Salesforce implementations and custom application development along with AI/ML working experience. Strong understanding of Large Language Models (LLMs), including model capabilities, limitations, prompt design, evaluation techniques, and enterprise AI use cases Experience designing and implementing Generative AI (GenAI) solutions using LLMs within Salesforce and enterprise ecosystems. Hands-on experience with Prompt Engineering, prompt optimization, prompt evaluation, grounding techniques, few-shot learning, and AI response quality improvement. Knowledge of Retrieval-Augmented Generation (RAG) architectures, vector databases, embeddings, semantic search, knowledge grounding, and enterprise knowledge systems. Deep understanding of Salesforce Architecture, including application design, integration architecture, security architecture, scalability patterns, governor limits, performance optimization, event-driven architecture, and reusable framework design. Proven experience integrating Salesforce with external systems using REST APIs, SOAP APIs, Platform Events, Change Data Capture (CDC), Streaming APIs, and Middleware platforms. Strong knowledge of Salesforce DevOps, deployment strategies, release management, Git Version Control, GitHub workflows, branching strategies, pull requests, code reviews, and CI/CD pipelines. Hands-on experience with GitHub Copilot and AI-assisted development tools to improve developer productivity, code quality, and automation. Experience with Agentforce, autonomous agents, agent orchestration, conversational workflows, and AI-powered business process automation. Experience in AI/ML Engineering, including model development, training, tuning, deployment, monitoring, and lifecycle management. Strong proficiency in Python for AI/ML development, automation, data processing, integration services, and backend engineering. Experience with Natural Language Processing (NLP) techniques such as text classification, entity extraction, sentiment analysis, summarization, and conversational AI systems. Hands-on experience with MLOps and LLMOps practices, including model versioning, experimentation, deployment automation, observability, monitoring, and governance. Experience deploying and monitoring machine learning and GenAI models in production environments, including performance tracking, model evaluation, drift detection, and optimization. Knowledge of cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP), including AI/ML and integration services. Experience building and maintaining data pipelines, ETL/ELT workflows, data ingestion frameworks, and enterprise data integration solutions. Understanding of Responsible AI, AI governance, security, privacy, compliance, explainability, bias mitigation, and ethical AI practices. Ability to design and deliver production-grade, s
Key Responsibilities
1. To architect| design and develop (through Team) solution for product/project & sustenance delivery
2. To support as an Subject Matter Expert
3. To ensure knowledge up-gradation and work with new technologies so that the solution is current and meets quality standards and the client requirements
4. Ensuring a sufficient pool of skilled professionals in the designated technology, through activities such as conducting interviews, providing training sessions and offering mentorship.
5. To gather specifications and deliver solutions to the client organization based on understanding of a domain or technology.
6. To support competency development with envisioning and articulating propositions â building collaterals/ whitepaper creation, market trend analysis etc.
7. To recommend client value creation initiatives and implement industry best practices (on specific technology/product)
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