Senior Ai Engineer (Python)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer (Python) based in Canada.
Join a high-performing engineering team to develop and enhance an enterprise AI platform that powers intelligent workflows, conversational experiences, and AI-driven automation across multiple business functions.In this role, you will design and build advanced AI agents and orchestration systems using Python, LangGraph, and LangChain.You will contribute to the development of scalable, production-ready generative AI solutions that streamline processes and deliver measurable business value.Working at the forefront of agentic AI, you will implement capabilities such as planning, memory management, tool calling, and multi-agent coordination.You will also integrate AI applications with enterprise systems and APIs while ensuring reliability, observability, and performance.Collaborating with cross-functional teams and stakeholders, you will help shape technical architecture, establish best practices, and accelerate innovation.This opportunity is ideal for an experienced AI engineer who enjoys solving complex challenges and building impactful AI solutions in a collaborative, globally connected environment.
Accountabilities
Develop, enhance, and maintain AI agents and orchestration capabilities using Python, LangGraph, and LangChain.
Build and extend AI-powered guided workflows and automation solutions that support diverse enterprise business functions.
Design, develop, and optimize conversational AI systems and chat-based applications for production environments.
Implement agent planning, orchestration, state management, memory, tool calling, and response-generation capabilities.
Integrate AI agents and applications with enterprise platforms, backend services, external systems, and APIs.
Support modern AI integration frameworks and agent communication patterns to enable effective collaboration between AI systems and enterprise applications.
Implement and improve AI observability, monitoring, telemetry, and performance-tracking mechanisms to evaluate system behavior and reliability.
Collaborate with engineering teams, product stakeholders, and other cross-functional partners to accelerate platform development and deliver business use cases.
Troubleshoot technical issues, optimize performance, strengthen solution reliability, and drive continuous improvements across the AI platform.
Contribute to architecture discussions, technical design decisions, engineering standards, and best practices for building scalable, maintainable AI solutions.
Help advance the adoption of emerging AI technologies and approaches to improve platform capabilities and support evolving business needs.
Requirements
At least 8 years of hands-on experience in Python development and enterprise application engineering.
At least 2 years of practical experience with LangGraph, including agent workflows, stateful orchestration, multi-agent systems, and AI-driven execution flows.
At least 2 years of experience with LangChain, including building large language model (LLM)-powered applications, integrating tools, implementing retrieval-augmented generation (RAG), and automating workflows.
Strong understanding of agentic AI concepts, including autonomous agents, planning, orchestration, memory management, and tool-calling frameworks.
Proven experience building, deploying, and maintaining production-grade generative AI applications.
Experience integrating AI-powered applications with enterprise platforms, backend services, and APIs.
Demonstrated ability to design and implement conversational AI and chat-based applications in production environments.
Familiarity with AI observability, monitoring, telemetry, evaluation frameworks, and performance analysis tools.
Strong knowledge of software engineering best practices, including code quality, testing, debugging, system design, and performance optimization.
Experience working in Agile development environments and collaborating effectively with multidisciplinary teams.
Excellent analytical and problem-solving abilities, with strong written and verbal communication skills.
Effective stakeholder management skills, with the ability to translate business needs into technical solutions and communicate complex concepts clearly.
A proactive, collaborative mindset, with an interest in emerging AI technologies, continuous learning, and delivering reliable, scalable solutions.
Nice to Have:
Hands-on experience with the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication standards.
Experience building, deploying, and maintaining multi-agent AI solutions in production environments.
Practical experience implementing RAG architectures and knowledge-based AI systems.
Familiarity with vector databases, embeddings, and semantic search technologies.
Experience working with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
Experience contributing to centralized enterprise AI platforms that support multiple business functions and use cases.
Exposure to healthcare or other highly regulated enterprise environments, with an understanding of the importance of security, reliability, and compliance.
Benefits
Competitive compensation and benefits: Access a comprehensive compensation package and employee benefits, including health insurance. Specific salary ranges and coverage details are not disclosed in the provided description.
Remote work flexibility: Benefit from a work-from-anywhere culture designed to support flexibility and work-life balance.
Professional development: Access learning opportunities, certification programs, mentorship, and talent development initiatives.
Career growth and internal mobility: Explore opportunities to expand your responsibilities, develop new expertise, and pursue career progression within the organization.
Global project exposure: Collaborate on impactful technology initiatives for major international clients and contribute to solutions that support business transformation.
International collaboration: Work alongside a multicultural, globally distributed team in an inclusive environment that values open communication and knowledge sharing.
Team engagement: Participate in team-building activities and social events that foster connection and collaboration.
Inclusive workplace culture: Join an environment that promotes equal opportunity, mutual respect, and support for professionals from diverse backgrounds.
Social responsibility: Contribute to sustainability initiatives focused on IT education, community empowerment, fair business practices, environmental responsibility, and gender equality.
Relocation support: A relocation program is offer
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