{"id":3538728,"url":"https://alion.io/job/derex-technologies-ai-architect-2","title":"AI Architect","company":{"id":6950,"name":"Derex Technologies","domain":"derextechnologies.com","url":"https://alion.io/company/derextechnologies","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":["CA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":85000,"max_usd":174000,"period":"year","method":"role_seniority_country_cell","sample_n":26},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"AutoGPT","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Cosmos DB","optional":false},{"name":"Azure DevOps","optional":false},{"name":"C#","optional":false},{"name":"Chain-of-Thought","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"CrewAI","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google AI Studio","optional":false},{"name":"Hugging Face","optional":false},{"name":"JavaScript","optional":false},{"name":"Keras","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-30T16:48:27Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-03T11:34:31Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Derex Technologies Inc specializes in providing IT consulting, staffing solutions and software services. Globally headquartered in Harrison New Jersey since 1996 Derex delivers the highest quality technology professionals and an array of customized IT talent solutions designed to improve productivity and drive results to global clients throughout North America.\nWith over two decades of unparalleled experience, Derex provides supports to its clientele, across such industries as Systems Integration, Banking and Finance, Telecommunications, Pharmaceutical and Life Sciences, Energy, Healthcare, Technology, Transportation, and local and federal Government agencies.\n About the job\nWe are seeking a visionary and highly experienced AI Architect to lead the design and delivery of next-generation intelligent solutions across our enterprise. This role is central to our digital transformation strategy and will focus on architecting robust, scalable, and secure AI-driven platforms and capabilities.\nAs an AI Architect, you will bring deep expertise in Artificial Intelligence, Machine Learning, Generative AI, Coding Assistants, AI Assistants, and Agile software engineering practices. You will guide the full AI lifecycle from conceptualization and solution design to model development, testing, and successful deployment into production environments. The ideal candidate will have a proven architectural background, hands-on experience with modern AI platforms, and a strong track record of delivering complex, enterprise-grade intelligent systems. You will collaborate closely with cross-functional technology and business teams to shape the future of our AI ecosystem and accelerate innovation across the organization.\nMust Have Skills:\nStrong hands-on programming expertise in at least one modern language such as Python, C#, Java, or JavaScript, with the ability to guide engineering teams on best practices.\nDeep proficiency with AI/ML frameworks and libraries including TensorFlow, PyTorch, and Keras, with the ability to architect scalable training and inference pipelines.\nAdvanced understanding of Generative AI architectures, including GANs, VAEs, transformer-based models, and experience applying these techniques to real-world enterprise use cases.\nPractical experience using AI Coding Assistants\nHands-on expertise with Agentic AI platforms, including Microsoft Copilot Agents, AutoGPT, CrewAI, Anthropic Claude, and other autonomous workflow systems.\nStrong command of Cloud & MLOps platforms, such as AWS SageMaker, Azure Machine Learning, Google AI Platform, including experience building automated model deployment, monitoring, and retraining pipelines.\nSolid experience architecting solutions on major cloud platforms (AWS, Azure, GCP), including familiarity with cloud-native AI, data, and security services.\nProven ability to mentor, guide, and provide architectural direction to junior and mid-level AI/ML engineers across multiple projects.\nAbility to conduct AI/ML and Generative AI code reviews, ensuring adherence to architectural standards, performance benchmarks, and responsible AI practices.\nStrong analytical and problem-solving skills, including the ability to rapidly diagnose and resolve complex issues in AI systems, ML pipelines, and application runtimes.\nExcellent communication skills, capable of translating complex AI concepts for both technical teams and business stakeholders.\nExperience defining enterprise AI architectures, reference models, reusable design patterns, and establishing organization-wide architectural standards.\nAbility to define and implement AI governance frameworks, including Responsible AI guidelines, compliance controls, model guardrails, safety protocols, and risk-mitigation practices.\nResponsibilities:\nAI & Machine Learning Architecture\nArchitect, design, and guide the implementation of enterprise grade AI and ML solutions that solve complex business problems and power intelligent applications.\nLead collaboration with data scientists, ML engineers, platform engineers, and software teams to integrate AI capabilities into products, platforms, and enterprise workflows.\nProvide hands-on technical leadership in Python, including proficiency with ML, GenAI, and LLM frameworks (TensorFlow, PyTorch, HuggingFace, LangChain, etc.).\nOversee end-to-end data preparation, feature engineering, vectorization, and model development, ensuring data quality and readiness for LLMs and Generative AI workloads.\nContinuously evaluate emerging advancements in AI, ML, LLMs, Agentic Systems, and incorporate relevant innovations into architectural roadmaps and solution designs.\nOptimize AI and Generative AI models for performance, latency, scalability, observability, and cost efficiency, leveraging cloud-native and distributed compute environments.\nConduct and drive technical design reviews, code reviews, and architecture assessments to ensure high standards of quality and engineering rigor.\nDiagnose, troubleshoot, and resolve complex AI system issues to maintain the reliability, accuracy, and security of production AI applications.\nGenerative AI, Copilots & Coding Assistants\nDesign and architect enterprise-wide capabilities leveraging AI coding assistants, copilots, and developer productivity tools (e.g., GitHub Copilot, Azure AI Studio assistants).\nLead the development of extensions, plugins, and integrations for IDEs like Visual Studio Code, IntelliJ IDEA, and Eclipse to embed AI-driven developer workflows.\nApply deep understanding of prompt engineering, LLM behaviour, context-window optimization, fine-tuning, and agentic workflows to enhance solution performance.\nDesign, train, and evaluate custom generative models, exploring architectures such as GANs, VAEs, diffusion models, and transformer-based architectures.\nArchitect pipelines for data acquisition, cleaning, text chunking, retrieval augmentation (RAG), and ingestion into vector stores.\nIntegrate enterprise solutions with AI platforms and APIs such as OpenAI, Azure OpenAI, LangChain, and other orchestration frameworks.\nDesign and maintain the LLM data layer using technologies like Azure Cosmos DB, Azure AI Search, vector stores, and embedding indexes.\nDevelop agentic automation solutions using frameworks such as LangChain, LlamaIndex, Semantic Kernel, and AutoGen, and integrate them with enterprise systems.\nApply strong DevOps practices using CI/CD pipelines, GitHub Actions, Azure DevOps, and modern testing frameworks to maintain robust and automated AI development workflows.\nContribute to or lead copilot initiatives across domains such as application development, customer support, operations, and productivity automation.\nPrompt Engineering\nDesign, test, and refine high-quality prompts, prompt templates, and generative AI interaction models tailored to organizational use cases.\nWork closely with product, content, and data teams to align prompt behaviour with business outcomes, brand voice, and user experience requirements.\nContinuously improve prompt structures to enhance accuracy, relevance, safety, and contextual understanding within AI/LLM systems.\nExperiment with novel prompting strategies-chain-of-thought, retrieval-augmented prompts, tool-augmented prompts, system message optimization-to improve AI performance.\nBuild and maintain an enterprise prompt library, ensuring versioning, governance, reuse, and integration into automated workflows and applications.\nParticipate in fine-tuning and reinforcement learning processes by designing ground-truth prompts, evaluation prompts, and tuning datasets.\nDiagnose and refine prompts that yield suboptimal or incorrect results, ensuring predictable and aligned LLM behaviour across use cases.\n All your information will be kept confidential according to EEO guidelines.","description_format":"text","description_chars":7792,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Staffing & Staff Augmentation"],"lifecycle":[{"event":"open","at":"2026-10-30T18:34:21Z"}],"visa":[],"liveness":{"score":75,"band":"hot","label":"Hiring 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