AI Solution Principal
Offre en anglaisDesign and build advanced agentic workflows and reusable technical components for Digital Employees using Claude and MCP tools. Create reference implementations and orchestration patterns to enable deployment by field engineering and go-to-market teams.
- Sur place
- ON
- Publié 20 août 2026
- Postuler avant le 19 sept. 2026
- 1 poste
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Résumé du poste
Job Overview We are seeking an AI Solution Principal I for the Anthropic Ecosystem team in Canada. This is a hands-on deep-tech role supporting the Distinguished Engineer, Agentic AI, and the MSAB pillar. The role will design and build advanced agentic workflows, MCP / tool integrations, orchestration patterns, and reusable technical components for Digital Employees. The candidate will create reference implementations that FDE teams can deploy and GTM teams can position with clients. This role is highly technical and delivery-enabling. It does not carry P&L or commercial ownership. Key Responsibilities Design and build advanced agentic workflows using Claude, MCP tools, and enterprise integration patterns. Build reusable MCP / tool integrations across enterprise systems, APIs, data platforms, workflow tools, and knowledge repositories. Create reference implementations that can be reused by FDE teams and positioned by GTM teams. Develop reusable Digital Employee components such as task planners, tool routers, approval flows, escalation logic, memory patterns, and domain workflows. Support the Distinguished Engineer in building and validating MSAB platform assets, architecture patterns, and reusable components. Define and implement agentic orchestration patterns for multi-agent workflows, human-in-the-loop processes, and tool-use governance. Support eval patterns, eval harnesses, observability, system design, performance tuning, and reliability engineering. Feed deep technical learnings from client work back into MSAB, CoE, field teams, and delivery teams. Support joint architecture work with Anthropic engineering team. Build technical blueprints, demo assets, prototypes, reusable code components, and implementation guides. Ensure reusable components meet standards for security, scalability, reliability, observability, and maintainability. Scope of Ownership Owns Advanced agentic workflow design and build MCP / tool integration implementation Reference implementations for FDE deployment Reusable Digital Employee components Agentic orchestration patterns Eval pattern implementation support Observability and performance tuning patterns System design support for MSAB assets Technical feedback loop into MSAB, CoE, and field teams Joint architecture contribution with Anthropic engineering Does Not Own P&L or commercial accountability GTM strategy - owned by Principal GTM FDE utilisation - owned by Director FDE Global Overall Agentic AI technical strategy - owned by Distinguished Engineer, Agentic AI Final commercial pricing and contracting Day-to-day FDE scheduling Client account ownership Required Skills and Experience 10+ years of experience in solution architecture, AI engineering, platform engineering, enterprise integration, software engineering, or advanced technical consulting. Strong hands-on experience designing and building GenAI, LLM, agentic AI, automation, or intelligent workflow solutions. Experience with Claude, LLM applications, prompt design, tool use, agent orchestration, and enterprise AI implementation patterns. Strong understanding of MCP-style integrations, secure tool access, permissions, APIs, and enterprise connectivity. Experience building reusable reference implementations, accelerators, prototypes, SDK components, or technical solution blueprints. Knowledge of evals, observability, logging, tracing, system reliability, and performance tuning for AI systems. Ability to design reusable Digital Employee components and agentic workflow patterns. Strong software engineering skills with experience in Python, TypeScript, APIs, cloud-native services, or integration frameworks. Ability to work across Distinguished Engineering, FDE, GTM, CoE, delivery, and partner engineering teams. Strong communication skills with the ability to explain complex technical topics clearly. Preferred Skills and Experience Experience with Anthropic, Claude, MCP, Agentic AI, Digital Employees, or enterprise AI assistants. Experience building multi-agent systems, tool-using agents, copilots, autonomous workflows, or enterprise AI agents. Experience with cloud platforms, vector databases, RAG, workflow orchestration, event-driven systems, and enterprise data platforms. Exposure to AI evaluation frameworks, model benchmarking, red-teaming, responsible AI, and quality gates. Experience in consulting, systems integration, SaaS, enterprise platform, or AI transformation environments. Experience supporting client demos, POCs, pilots, and production deployments. Experience working with strategic technology partners or partner engineering teams.
Ce que vous ferez
Design and build advanced agentic workflows and reusable technical components for Digital Employees using Claude and MCP tools. Create reference implementations and orchestration patterns to enable deployment by field engineering and go-to-market teams.
Exigences
Requires over 10 years of experience in solution architecture or AI engineering with strong hands-on expertise in GenAI and LLM applications. Proficiency in Python, TypeScript, and enterprise integration patterns is essential.
Compétences indiquées
- TypeScriptSouhaitée
- PythonSouhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Agentic AI
- Solution Architecture
- Claude
- Model Context Protocol (MCP)
- Python
- TypeScript
- LLM Orchestration
- Enterprise Integration
- Prompt Design
- RAG
- Vector Databases
- AI Evaluation
- Observability
- System Design
- Cloud-Native Services
- API Development
Domaines d’emploi
- Technology
- Software
- Engineering
- Consulting
- Data & Analytics
Renseignements supplémentaires
- Expérience minimale
- 10+ ans
- Postuler avant le
- 19 sept. 2026
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Niveau d’expérience
- Mid-Senior level
- Mode de candidature
- La candidature directe est offerte