AI Engineer

Ellison Institute of Technology; Town of Oxford; Presencial; CAD 90.000 - 140.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Enhanced holiday pay

Pension

Life Assurance

Income Protection

Private Medical Insurance

Hospital Cash Plan

Therapy Services

Perk Box

Electric Car Scheme

Descripción de la vacante

The Ellison Institute of Technology (EIT) is seeking a hands-on engineer to join the AI and Robotics team in Nova Scotia. You will build agent skills, integrate tools and evaluate workflows to support protein design and enzyme engineering, helping researchers plan experiments and produce evidence for testing.

Reporting to the Lead Software Engineer, you will collaborate with product managers, scientists and platform teams to extend our agent framework, ensure robust data handling, and deliver

Formación

• You have shipped multi-step agentic workflows with tool integrations and context management.
• You have built reusable agent skills or tool interfaces, for example with MCP.
• You write APIs and data-handling code with automated tests and version control.
• You have integrated tools or services and handled invalid inputs, asynchronous execution and partial failures.
• You can turn examples and failure cases into repeatable evaluations. You use evaluation results to change how an agent behaves, not just to report on it.
• You can work with domain experts and turn unfamiliar requirements into testable software.

Responsabilidades

• Turn scientific objectives and constraints into agent instructions, tool inputs and candidate checks, working with scientists and product managers.
• Build agent workflows that retrieve relevant evidence, propose design steps and explain assumptions, uncertainties and decisions requiring scientific review.
• Integrate scientific tools, models and calculators; validate inputs, interpret outputs and handle failures.
• Connect workflows to data storage, compute, approval and progress-reporting capabilities, working with the data and platform teams.
• Implement candidate generation, filtering and ranking against agreed criteria. Prepare sequences and supporting results for scientist review and experimental testing, including gene synthesis where required.
• Build workflow-specific reference cases and regression checks using shared evaluation tooling. Compare permitted models and configurations for task quality, completion, speed and cost.
• Investigate failures in reasoning, tool use and execution; improve agent instructions, context handling and code using evaluation results and scientist feedback.
• Record input references, tool and model versions, parameters and output locations so results can be inspected and reproduced.
• Write tested, maintainable code, contribute to reviews and support deployed workflows. Reuse components as scientific programmes expand.

Conocimientos

Agent workflows

Tool integrations

APIs and data handling

Containers and cloud compute

Herramientas

MCP

Descripción del empleo

Job Summary

Join EIT's AI and Robotics team to build AI agents that help scientists plan and carry out research. Our LifeAI platform connects models, scientific tools, data and compute so researchers can investigate questions, run analyses and review results.

You will build agent skills, tool integrations and evaluations, initially for protein design and enzyme engineering. Your work will help agents propose workflows, explain their assumptions, execute reviewed plans and produce candidates and evidence for experimental testing.

Reporting to the Lead Software Engineer, you will work with scientific product managers, researchers and platform teams. You will build on EIT's existing agent framework and scientific tools, with programme scientists providing domain guidance and scientific review. This is a hands‑on engineering role focused on making AI useful in research.

Key Responsibilities

• Turn scientific objectives and constraints into agent instructions, tool inputs and candidate checks, working with scientists and product managers.
• Build agent workflows that retrieve relevant evidence, propose design steps and explain assumptions, uncertainties and decisions requiring scientific review.
• Integrate scientific tools, models and calculators; validate inputs, interpret outputs and handle failures.
• Connect workflows to data storage, compute, approval and progress-reporting capabilities, working with the data and platform teams.
• Implement candidate generation, filtering and ranking against agreed criteria. Prepare sequences and supporting results for scientist review and experimental testing, including gene synthesis where required.
• Build workflow-specific reference cases and regression checks using shared evaluation tooling. Compare permitted models and configurations for task quality, completion, speed and cost.
• Investigate failures in reasoning, tool use and execution; improve agent instructions, context handling and code using evaluation results and scientist feedback.
• Record input references, tool and model versions, parameters and output locations so results can be inspected and reproduced.
• Write tested, maintainable code, contribute to reviews and support deployed workflows. Reuse components as scientific programmes expand.

Essential Knowledge, Skills, and Experience

If you meet most of these, we'd like to hear from you.

• You have shipped multi-step agentic workflows with tool integrations and context management.
• You have built reusable agent skills or tool interfaces, for example with MCP.
• You write APIs and data‑handling code with automated tests and version control.
• You have integrated tools or services and handled invalid inputs, asynchronous execution and partial failures.
• You can turn examples and failure cases into repeatable evaluations. You use evaluation results to change how an agent behaves, not just to report on it.
• You can work with domain experts and turn unfamiliar requirements into testable software.

Desirable Knowledge, Skills, and Experience

These are optional; you do not need to meet them to apply.

• Familiarity with protein design, enzyme engineering, computational biology or scientific software.
• Experience integrating sequence or structure analysis, molecular modelling or protein‑design tools.
• Experience with literature retrieval, evidence‑linked reporting or scientific data formats.
• Familiarity with workflow engines, containers, cloud or HPC compute, and data‑access controls.

We offer the following salary and benefits:

• Enhanced holiday pay
• Pension
• Life Assurance
• Income Protection
• Private Medical Insurance
• Hospital Cash Plan
• Therapy Services
• Perk Box
• Electric Car Scheme

Why work for EIT:

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!