Senior AI Engineer

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June 13

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Tecknoworks

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SaaS • Artificial Intelligence • Enterprise

Tecknoworks is a leading technology company that provides innovative cloud solutions, AI business solutions, and data analytics services. With a strong focus on Microsoft Azure, Tecknoworks delivers customized solutions to empower businesses through digital transformation. The company's expertise spans across software and app development, process automation, and the integration of AI tools, ensuring comprehensive cloud-based automation and data management. Tecknoworks is also recognized for its robust data security, compliance, and strong partnerships with Microsoft, offering services tailored for healthcare, business intelligence, and various industries looking to enhance their operational capabilities through cutting-edge technology.

51 - 200 employees

☁️ SaaS

🤖 Artificial Intelligence

🏢 Enterprise

📋 Description

• Tecknoworks is the boutique technology consulting firm of choice for innovative organizations across North America and Western Europe. • We're seeking a Senior AI Engineer to join our established AI practice and work directly on immediate client projects. • You'll contribute to our continued success in delivering intelligent automation solutions while collaborating closely with our experienced AI team. • Architect enterprise-scale AI solutions for complex client challenges across various industries. • Lead complex multi-model AI implementations that integrate LLMs, traditional ML, and business systems. • Conduct client workshops and technical deep-dives to identify AI opportunities and design solutions. • Present technical concepts confidently to both technical teams and C-level executives. • Manage client relationships and expectations throughout AI project lifecycles. • Design and implement sophisticated AI systems including RAG architectures, multi-model orchestration, and hybrid ML/LLM solutions. • Build production-ready AI applications with comprehensive monitoring, governance, and scalability. • Optimize model performance and costs across cloud platforms (Azure AI/AWS SageMaker). • Implement enterprise MLOps pipelines with automated training, deployment, and monitoring. • Research and evaluate emerging AI technologies for client applications. • Collaborate closely with the existing AI team to deliver complex client projects. • Define AI best practices and standards for the organization. • Mentor junior AI engineers and cross-functional team members. • Lead cross-functional AI transformation projects involving data, software, and business teams.

🎯 Requirements

• 5+ years of hands-on AI/ML experience with production deployments • Advanced proficiency in both traditional machine learning and large language models • Proven experience with LLM operations: prompt engineering, fine-tuning, RAG implementations, and multi-modal integration • Strong MLOps capabilities: end-to-end ML pipelines, model monitoring, A/B testing, and automated retraining • Cloud AI platforms: Advanced experience with Azure AI Services or AWS SageMaker, including cost optimization and governance • Programming: Expert-level Python, experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.) • LLM Technologies: OpenAI, Anthropic, Azure OpenAI, Hugging Face, vector databases, embedding strategies • Data Engineering: Experience with data pipelines, feature stores, and data quality for AI applications • Enterprise Integration: API development, microservices, containerization (Docker/Kubernetes) • Strong problem-solving abilities with experience breaking down complex, ambiguous business challenges into manageable AI solutions • Proven track record of leading technical client engagements and presenting to executive audiences • Strong business acumen with the ability to translate business problems into AI solutions • Excellent communication skills in English for international client interactions • Experience in gathering requirements, solution architecture, and managing technical delivery • Advanced degree in Computer Science, AI/ML, Data Science, or related field • Industry certifications in cloud AI platforms (Azure AI Engineer, AWS ML Specialty) • Consulting experience in technology or AI advisory roles • Research contributions through publications, conferences, or open-source projects • Experience with specific industries (healthcare, pharma, finance, retail, manufacturing)