Generative AI Developer (ID#5477)

New Value Solutions, a national IT consulting company, is seeking a Generative AI Developer to join our client’s Innovation Team. This hands-on role will work with a cross-functional team to explore, prototype, and implement generative and agentic AI technologies that solve complex business problems. The successful candidate will bring a strong software development foundation, practical experience integrating large language models (LLMs), and an interest in advancing AI-native engineering practices across the organization.We recognize that agentic AI is an emerging field. Candidates without direct multi-agent project experience are encouraged to apply if they offer a strong combination of relevant LLM, AI architecture, cloud, and software development experience.ResponsibilitiesDesign, prototype, and build applications using OpenAI, Azure OpenAI, and open-source LLMsDevelop, optimize, and operationalize Retrieval-Augmented Generation (RAG) and GraphRAG pipelinesExplore and implement agentic and multi-agent system patterns using tools such as AutoGen, LangChain, and Semantic KernelIntegrate LLM-based solutions into enterprise workflows, applications, and digital productsDesign solutions using embeddings and vector databases such as Qdrant, pgvector, and Azure Cosmos DBLeverage Azure AI services and models to improve solution capabilities, scalability, and performanceDevelop prompt strategies, memory-management approaches, task-chaining workflows, and model evaluation practicesCollaborate with product teams, developers, data scientists, and business stakeholders to identify, test, refine, and deliver AI use casesTransition validated proofs of concept into secure, reliable, production-grade applicationsEstablish and continuously improve an AI-native Software Development Lifecycle (AI-SDLC), including standards, guardrails, and best practicesIntegrate AI tools into development workflows, including code generation, automated testing, documentation, debugging, validation, and code reviewDevelop reusable reference architectures, delivery pipelines, templates, components, and AI development patternsEstablish AI-assisted quality and reliability practices, including automated test generation, model-aware reviews, evaluation frameworks, and AI-enabled CI/CD checksMeasure and report on AI-SDLC outcomes, including delivery speed, cycle time, defect reduction, developer productivity, and adoptionMaintain clear technical documentation covering models, prompts, workflows, architecture, evaluations, and key decisionsProvide regular stakeholder updates, demonstrations, and presentationsParticipate in Agile ceremonies, architecture discussions, code reviews, and DevOps practicesMentor junior developers and promote knowledge sharing and consistent adoption of AI-native engineering practicesStay current with emerging research, tools, and best practices in generative AI, agentic systems, and AI-enabled software developmentRequirements5+ years of software development experience, including recent experience with LLMs, generative AI, or AI integrationsStrong proficiency in Python and experience with AI/ML frameworks and tools such as OpenAI SDKs, LangChain, and Hugging FaceExperience with C#, .NET Core, and object-oriented designUnderstanding of agent-based architecture concepts and tools such as AutoGen or Semantic KernelExperience with RAG, GraphRAG, embeddings, prompt engineering, and vector databases such as Cosmos DB, pgvector, or QdrantExperience designing and integrating REST APIs and enterprise applicationsExperience deploying cloud-based solutions, preferably within Microsoft AzureKnowledge of Git, CI/CD pipelines, DevOps practices, and Agile software developmentExperience designing or implementing AI-enabled SDLC practices, including developer copilots, automated test generation, AI-assisted code review, and intelligent documentation workflowsAbility to evaluate emerging AI tools and translate promising concepts into practical, production-ready solutionsStrong analytical and problem-solving skills, with the ability to synthesize complex informationExcellent communication skills and the ability to explain AI capabilities, limitations, and architectural decisions to technical and non-technical audiencesDemonstrated ability to collaborate across disciplines, mentor other developers, and contribute to technical standards and architecture decisionsBachelor’s degree in Computer Science or a related STEM fieldIf you have the necessary expertise and able to work in Canada, please submit your resume. While we thank all candidates in advance for their application, only those shortlisted will be contacted.ID#5477