{"id":504339,"url":"https://alion.io/job/sia-generative-ai-consultant-2","title":"Generative AI Consultant","company":{"id":5732,"name":"Sia","domain":"sia.com","url":"https://alion.io/company/sia","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":53,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":80000,"max":100000,"currency":"CAD","period":"year","gross":null,"usd_annual":70030},"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"EU AI Act","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Gemini","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Mistral","optional":false},{"name":"Mistral SDK","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NER","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Sentiment Analysis","optional":false},{"name":"VLM","optional":false},{"name":"AI Agents","optional":true},{"name":"AutoGen","optional":true},{"name":"Chroma","optional":true},{"name":"LangGraph","optional":true},{"name":"OpenSearch","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PostgreSQL","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-04-17T19:36:15Z","employer_posted_date":"2026-04-17","last_verified_at":"2026-10-18T10:18:47Z","board_verified":true,"closed_at":null,"days_open":183,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":183},"description":"About Sia\nSia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.\nSia’s AI & Data Business Unit is the powerhouse of our firm’s innovation-merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia’s AI & Data team, you’ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting.\n Join us as an experienced Generative AI Specialist designing and implementing cutting-edge GenAI/LLM solutions across diverse industries. You'll act as a vital bridge between technical teams (Data Science, ML, Platform) to deliver business-centric AI value. You'll guide clients on the optimal path-using techniques like RAG, agents, or fine-tuning-for cost-effective impact.\nYour responsibilities extend beyond prompting to architecting robust AI products via benchmarking, prototyping, and validation. You'll orchestrate the full AI workflow, ensuring seamless model integration optimized for performance, security, and scale, while tackling infrastructure challenges. We provide extensive training to support your success. If you're driven to push AI boundaries and help clients rapidly adopt GenAI with confidence, apply to make a real difference.\nResponsibilities:\nLLM/GenAI System Development: Design, build, train, fine-tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT-x, Claude, Gemini, Llama, Mistral) and other generative techniques. \nAssist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications. \nApplication Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.). \nAdvanced Prompt Engineering: Design and optimize effective prompts (e.g., few-shot, Chain/Tree/Graph of Thought, ReAct, Self-reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions. \nRAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre-determined knowledge sources, providing traceability (source attribution). \nModel Selection & Fine-Tuning: Select and fine-tune appropriate models (including multimodal - VLM, SLM - Visual Language Models, Small Language Models) to create higher-quality content (text, image, audio, code, etc.) and maximize business value creation opportunities. \nIntegration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP). \nEvaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end-to-end security and compliance processes. \nResearch & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing. \nCollaboration: Work effectively within cross-functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non-technical). \nDocumentation: Document processes, methodologies, and best practices for knowledge sharing and future reference. \nUse Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis). \n Education:\nMaster's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field. \nExperience: 1-3+ years of hands-on experience in machine learning, software engineering, or data science, with demonstrated experience on complex AI projects specifically involving LLMs and Generative AI. \nRequired Technical Skills:\nStrong programming skills, particularly in Python. \nProficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.). \nProven experience in NLP/NLU, vector embeddings, and semantic search. \nHands-on experience with fine-tuning LLMs. \nMastery of advanced prompting techniques (Chain/Tree/Graph of Thought, ReAct, etc.). \nKnowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, models hosted on AWS/Azure/GCP, etc.). \nExperience with Cloud platforms (AWS, Azure, or GCP) and their associated MLOps/AI services. \nFamiliarity with MLOps principles, CI/CD tools, Docker, and Git. \nSoft Skills:\nExcellent communication skills (written and verbal), ability to explain complex technical concepts simply. \nStrong analytical and complex problem-solving abilities. \nTeam player with the ability to collaborate effectively with diverse profiles. \nCuriosity, pioneering spirit, and a demonstrated commitment to continuous learning. \nPreferred Qualifications:\nExperience building agentic AI systems (e.g., LangGraph, AutoGen). \nExperience with vector databases (e.g., pgvector, Pinecone, Chroma, OpenSearch). \nExperience developing conversational AI systems / chatbots. \nFamiliarity with deep learning frameworks (PyTorch, TensorFlow). \nUnderstanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as Model Context Protocol (MCP). \nExperience deploying models at scale in production environments. \n Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.\nSia is an equal opportunity employer. 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