Blend360
AI services
SeniorAIEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Senior AI Engineer at Blend360. Skills: AI/ML engineering, generative AI, Python, RAG, agentic workflows, cloud deployment, Microsoft Azure, LLM integration. production implementation of AI prototypes and pilot solutions. design, build, and maintain scalable AI applications”
What You'll Achieve.
co-creating meaningful impact for its clients; unlocking value and fostering innovation for its clients; creating more fulfilling work and projects for our people and clients; production implementation of AI prototypes and pilot solutions; transform them into secure, reliable, production-ready systems; engineering them into robust, scalable applications suitable for enterprise production environments; ensuring operational readiness
Industry & Context.
tackles significant challenges; unlocking value
Travel opportunities to attend industry conferences and meet clients
What They're Looking For.
Must Have
5+ years of software engineering experience, significant recent experience in AI/ML engineering and generative AI applications, proficiency in Python, modern backend development practices, Proven experience designing and implementing RAG architectures in production environments, Hands-on experience with agentic AI workflows, orchestration frameworks, and tool-using autonomous systems, Experience working with LLM APIs such as those from OpenAI and Anthropic, cloud experience with Microsoft Azure, including deployment, infrastructure, and managed AI services, Full-stack engineering experience, with the ability to work across backend services and front-end integration layers, Experience taking solutions from prototype to production, including scaling, hardening, and operational support, Advanced English proficiency
Nice to Have
Experience with containerization and orchestration technologies (Docker, Kubernetes), Familiarity with vector databases, embeddings, and semantic search architectures, Knowledge of enterprise security and governance considerations for AI systems, Experience in consulting or delivery-center models supporting global teams
What You'll Do.
production implementation of AI prototypes and pilot solutions
and maintain scalable AI applications
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines
Build and manage agentic workflows
Deploy AI services in cloud-native environments
Integrate and operationalize large language models
Contribute to full-stack development
Apply software engineering best practices
How You'll Work.
Team & Collaboration
Collaborate across engineering, architecture, and client-facing teams; supporting global teams
Communication Scope
English proficiency; professional communication
Full Job Description
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit [www.blend360.com](http://www.blend360.com/) We are seeking a Senior AI Engineer to join a high-impact delivery team supporting the productionization of advanced AI solutions for enterprise clients. This role is ideal for someone with strong hands-on experience building scalable AI applications, particularly in generative AI, and who can take early-stage prototypes and transform them into secure, reliable, production-ready systems. The Senior AI Engineer will work closely with an on-site innovation team that develops initial proofs of concept and prototype solutions. Once those solutions are validated, they will transition to the Delivery Center team, where this role will be responsible for engineering them into robust, scalable applications suitable for enterprise production environments. This includes designing architecture, improving performance, implementing best practices, and ensuring operational readiness. Key Responsibilities * Take AI prototypes and pilot solutions developed by on-site teams and lead their end-to-end production implementation. * Design, build, and maintain scalable AI applications using Python as the primary programming language. * Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases, including document retrieval, knowledge orchestration, and contextual response generation. * B
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