Staff Forward Deployed Engineer, AI Simulation in Canada Creek, Nova Scotia at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Forward Deployed Engineer, AI Simulation in Canada.

This role sits at the intersection of advanced AI systems, scientific computing, and real-world client delivery, acting as a critical technical bridge between core research models and high-impact external deployments. You will work directly with scientific teams to translate complex computational and simulation challenges into scalable, production-grade solutions. Operating in highly ambiguous, fast-moving environments, you will own end-to-end technical execution across client engagements, from architecture through deployment. The position combines deep engineering expertise with strong problem-solving autonomy and cross-functional collaboration. You will help integrate cutting-edge AI and simulation technologies into real scientific and industrial workflows. This is a hands-on role where engineering rigor meets frontier science and applied impact.

In this role, you will take ownership of technical delivery across complex AI simulation engagements, working closely with researchers, engineers, and product stakeholders to ensure successful execution of high-impact projects. You will design, build, and deploy scalable systems that support scientific workflows, while also driving integration of advanced AI models and simulation tools into client environments.

• Lead end-to-end technical execution of client deployments, diagnosing bottlenecks and ensuring successful delivery of scientific and AI-driven solutions
• Architect and develop high-performance systems to extend simulation tools, automate R&D workflows, and support large-scale computation
• Serve as a technical translator between scientific researchers and engineering teams, ensuring alignment between experimental needs and system design
• Build and maintain cloud infrastructure, data pipelines, and deployment systems with a focus on scalability, reliability, and performance
• Integrate internal AI systems, including large quantitative models and agent-based frameworks, into bespoke external environments
• Collaborate across functions to validate solutions against scientific requirements and production constraints

The ideal candidate brings extensive backend and systems engineering experience, with strong proficiency in Python and modern distributed architectures. You should be comfortable operating independently in high-ambiguity environments and have a proven ability to deliver complex systems end-to-end. Experience in cloud infrastructure, workflow orchestration, and production-grade software engineering is essential, along with strong communication skills to bridge technical and non-technical teams.

• 7+ years of software engineering experience with strong expertise in Python and scalable system design
• Proven ability to work independently in fast-paced, ambiguous environments with high ownership expectations
• Hands-on experience with cloud orchestration tools such as Kubernetes and workflow systems like Airflow
• Strong background in REST APIs, database systems (SQL, ORM, schema design), and Infrastructure as Code (Terraform)
• Experience building production-grade systems in customer-facing or research-driven environments
• Strong communication skills with the ability to translate complex technical concepts across diverse stakeholders
• Nice to have: experience in cheminformatics, drug discovery, HPC, GPU computing, or AI agent systems

• Competitive base salary with performance-based incentives and equity participation
• Comprehensive medical, dental, and vision coverage for employees and dependents
• Retirement savings plans with employer contributions
• Flexible paid time off and company-wide seasonal breaks
• Remote-first flexibility with support for sustainable work arrangements
• Parental leave and inclusive family-building benefits
• Learning and development budget with opportunities for continuous growth and cross-functional exposure