{"schemaVersion":"jobsearcher.job.v1","id":"9dfb5a9d744fede6d7ea4bd3","url":"https://jobsearcher.com/jobs/9dfb5a9d744fede6d7ea4bd3","canonicalUrl":"https://jobsearcher.com/jobs/9dfb5a9d744fede6d7ea4bd3","title":"Senior Software Developer - Generative AI","description":"Senior Software Developer - Generative AI\n\nOur client is seeking a Intermediate to Senior Generative AI Developer with a strong foundation in working with large language models (LLMs) and a keen interest in building intelligent, agentic systems. As part of the Innovation Team you’ll be working with a cross-functional team to explore, prototype, and implement artificial intelligence technologies to solve complex business problems. This is a hands-on role focused on rapid prototyping, integration, and advancing the practical use of generative AI across business processes.\n\nWe recognize that agentic AI is an emerging domain. If direct project experience is not available, we encourage applications from candidates with the most applicable mix of skills, curiosity, and relevant experience in LLMs, AI architecture, and software development.\nSpecific Responsibilities and Deliverables:\nDesign and build applications using OpenAI, Azure OpenAI, and open-source LLMs\nDevelop and optimize Retrieval-Augmented Generation (RAG) pipelines\nExplore and implement foundational patterns for multi-agent AI systems using tools like AutoGen, LangChain, or Semantic Kernel\nIntegrate LLMs into enterprise workflows and digital products\nUse vector databases such as Qdrant, pgvector, and Cosmos DB\nLeverage Azure AI services and models to enhance capabilities and performance\nCollaborate with product teams and data scientists to test, refine, and deliver AI use cases\nDevelop prompt strategies, memory handling, and task chaining\nMaintain clear documentation of models, architecture, and decision-making\nStay current with research and best practices in generative and agentic AI\nCollaborate with cross-functional teams to transition validated concepts to production\nParticipate in Agile ceremonies, code reviews, and DevOps practices\nMaintain technical documentation and participate in system architecture decisions\nProvide mentorship to junior developers and support knowledge sharing\nEstablish and evolve AI-native Software Development Lifecycle practices, including integrating AI tools into development workflows (code generation, testing, documentation, debugging, and review) to improve delivery speed, quality, and developer productivity\nPrototype and operationalize AI-driven development workflows, evaluating emerging tools and approaches for AI-native software engineering and integrating them into the team’s SDLC where appropriate\nDeliverables:\nPrototypes and fully developed, production-grade applications that demonstrate generative and agentic AI capabilities\nIntegration of LLM-based solutions into existing enterprise environments\nDocumentation of models, prompts, workflows, and architectures\nRegular stakeholder updates and demo presentations\nContributions to reusable components and AI development patterns\nAI-Native Software Development Lifecycle (AI-SDLC):\nDesign, implementation, and continuous improvement of an AI-native Software Development Lifecycle (AI-SDLC), defining standards, guardrails, and best practices for building AI-enabled solutions\nIntegration of AI tools into day-to-day development workflows (e.g., code generation, testing, documentation, debugging, and review) to measurably improve delivery speed, quality, and developer productivity\nEstablishment of AI-assisted quality and reliability practices, including automated test generation, AI-supported validation, and model-aware review processes\nDevelopment of reference architectures, pipelines, and templates for AI-enabled delivery (e.g., prompt management, evaluation, CI/CD with AI checks)\nMeasurement and reporting of AI-SDLC effectiveness, such as productivity gains, defect reduction, cycle-time improvements, and developer adoption\nEnablement of teams through guidance, examples, and coaching to drive consistent adoption of AI-native engineering practices across initiative\nMandatory Requirements:\nBachelor’s degree in Computer Science or a related STEM field\n5–7 years of software development experience, including recent work with LLMs or AI integration\nProficiency in Python and experience with AI/ML frameworks (e.g., OpenAI SDKs, LangChain, Hugging Face)\nExperience in C#, .NET Core, and object-oriented design\nInterest and understanding of agent-based design concepts and tools (AutoGen, Semantic Kernel, etc.)\nFamiliarity with RAG, GraphRAG, embeddings, and vector databases such as Cosmos DB, pgvector, or Qdrant\nExperience deploying solutions to the cloud (Azure preferred)\nKnowledge of APIs, CI/CD pipelines, Git, and Agile software development practices\nAbility to synthesize complexity and communicate AI capabilities clearly to diverse audiences\nExperience designing or implementing AI-enabled Software Development Lifecycle (AI-SDLC) practices, including developer copilots, automated test generation, AI-assisted code review, and intelligent documentation workflows\nSenior Software Developer - generative AI Assignment Length\n12 months\nSenior Software Developer - Generative AI Assignment Location\nRichmond, BC -3 days in office","company":"Procom","rawCompany":"procom","city":"Richmond","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-09T14:55:02.674Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Software Developer - Generative AI","description":"Senior Software Developer - Generative AI\n\nOur client is seeking a Intermediate to Senior Generative AI Developer with a strong foundation in working with large language models (LLMs) and a keen interest in building intelligent, agentic systems. As part of the Innovation Team you’ll be working with a cross-functional team to explore, prototype, and implement artificial intelligence technologies to solve complex business problems. This is a hands-on role focused on rapid prototyping, integration, and advancing the practical use of generative AI across business processes.\n\nWe recognize that agentic AI is an emerging domain. If direct project experience is not available, we encourage applications from candidates with the most applicable mix of skills, curiosity, and relevant experience in LLMs, AI architecture, and software development.\nSpecific Responsibilities and Deliverables:\nDesign and build applications using OpenAI, Azure OpenAI, and open-source LLMs\nDevelop and optimize Retrieval-Augmented Generation (RAG) pipelines\nExplore and implement foundational patterns for multi-agent AI systems using tools like AutoGen, LangChain, or Semantic Kernel\nIntegrate LLMs into enterprise workflows and digital products\nUse vector databases such as Qdrant, pgvector, and Cosmos DB\nLeverage Azure AI services and models to enhance capabilities and performance\nCollaborate with product teams and data scientists to test, refine, and deliver AI use cases\nDevelop prompt strategies, memory handling, and task chaining\nMaintain clear documentation of models, architecture, and decision-making\nStay current with research and best practices in generative and agentic AI\nCollaborate with cross-functional teams to transition validated concepts to production\nParticipate in Agile ceremonies, code reviews, and DevOps practices\nMaintain technical documentation and participate in system architecture decisions\nProvide mentorship to junior developers and support knowledge sharing\nEstablish and evolve AI-native Software Development Lifecycle practices, including integrating AI tools into development workflows (code generation, testing, documentation, debugging, and review) to improve delivery speed, quality, and developer productivity\nPrototype and operationalize AI-driven development workflows, evaluating emerging tools and approaches for AI-native software engineering and integrating them into the team’s SDLC where appropriate\nDeliverables:\nPrototypes and fully developed, production-grade applications that demonstrate generative and agentic AI capabilities\nIntegration of LLM-based solutions into existing enterprise environments\nDocumentation of models, prompts, workflows, and architectures\nRegular stakeholder updates and demo presentations\nContributions to reusable components and AI development patterns\nAI-Native Software Development Lifecycle (AI-SDLC):\nDesign, implementation, and continuous improvement of an AI-native Software Development Lifecycle (AI-SDLC), defining standards, guardrails, and best practices for building AI-enabled solutions\nIntegration of AI tools into day-to-day development workflows (e.g., code generation, testing, documentation, debugging, and review) to measurably improve delivery speed, quality, and developer productivity\nEstablishment of AI-assisted quality and reliability practices, including automated test generation, AI-supported validation, and model-aware review processes\nDevelopment of reference architectures, pipelines, and templates for AI-enabled delivery (e.g., prompt management, evaluation, CI/CD with AI checks)\nMeasurement and reporting of AI-SDLC effectiveness, such as productivity gains, defect reduction, cycle-time improvements, and developer adoption\nEnablement of teams through guidance, examples, and coaching to drive consistent adoption of AI-native engineering practices across initiative\nMandatory Requirements:\nBachelor’s degree in Computer Science or a related STEM field\n5–7 years of software development experience, including recent work with LLMs or AI integration\nProficiency in Python and experience with AI/ML frameworks (e.g., OpenAI SDKs, LangChain, Hugging Face)\nExperience in C#, .NET Core, and object-oriented design\nInterest and understanding of agent-based design concepts and tools (AutoGen, Semantic Kernel, etc.)\nFamiliarity with RAG, GraphRAG, embeddings, and vector databases such as Cosmos DB, pgvector, or Qdrant\nExperience deploying solutions to the cloud (Azure preferred)\nKnowledge of APIs, CI/CD pipelines, Git, and Agile software development practices\nAbility to synthesize complexity and communicate AI capabilities clearly to diverse audiences\nExperience designing or implementing AI-enabled Software Development Lifecycle (AI-SDLC) practices, including developer copilots, automated test generation, AI-assisted code review, and intelligent documentation workflows\nSenior Software Developer - generative AI Assignment Length\n12 months\nSenior Software Developer - Generative AI Assignment Location\nRichmond, BC -3 days in office","datePosted":"2026-08-09T14:55:02.674Z","dateModified":"2026-08-09T14:55:02.674Z","hiringOrganization":{"@type":"Organization","name":"Procom","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Richmond","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"9dfb5a9d744fede6d7ea4bd3"},"url":"https://jobsearcher.com/jobs/9dfb5a9d744fede6d7ea4bd3"}}