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Niche PIM+LLM skillset and domain specificity reduce applicant density despite Bangalore location.
Role demands domain-specific PIM expertise, Inriver experience, and enterprise LLM skills, limiting cross-industry transferability.
Explicit 6–8 years requirement, mandatory C#/.NET, Azure/LLM, and PIM experience create strict filtering.
Lead development and optimization of AI-enhanced Product Information Management (PIM) workflows using Inriver Inspire AI and large language models to improve product content quality and speed-to-market.
Design and implement automated data transformation, validation, and import processes including AI agent-driven workflows and bulk data onboarding with integration to multiple systems via REST APIs and messaging patterns.
Evaluate and operationalize AI/ML tools to enhance productivity in product content lifecycle, ensuring compliance with enterprise AI governance, ethical guidelines, and security policies.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience.
6–8 years of engineering experience with C#/.NET, REST APIs, and MS SQL Server.
Minimum 2+ years hands-on experience building AI-driven applications including working with LLM workflows, prompt orchestration, RAG pipelines, or AI content generation.
Experience with AI agent frameworks (e.g., Azure AI Orchestration, Semantic Kernel, Lang Chain), Azure OpenAI or similar LLM platforms, and strong understanding of enterprise AI patterns such as retrieval-augmented generation and human-in-the-loop review.
Demonstrated expertise in complex PIM systems with knowledge of data modeling, enrichment workflows, validation, localization, and taxonomy, preferably with Inriver PIM experience including AI feature tuning and workflow customization.
Experience designing scalable, maintainable AI solution architectures in enterprise environments, including multi-agent coordination, workflow orchestration, and evaluation frameworks like embeddings tuning and vector search.
Proven ability to bridge engineering and cross-functional teams (Product Marketing, data governance) to implement AI-enabled automation pipelines and maintain governance, compliance, and operational excellence within Agile/Scrum settings.