Senior AI Software Engineer building agentic AI harnesses for Kinaxis’s Databricks - based enterprise data fabric. Enabling secure, governed workflows across GCP and Azure.
About the role
- Senior AI Engineer role at Keyrus focused on delivering AI solutions and leading a team. Engage with clients to translate business needs into AI strategies and solutions.
Responsibilities
- Translate business objectives into AI solutions — work directly with clients and stakeholders (executives, managers, and technical teams) to understand challenges, quantify value, and define success metrics before building.
- Lead platform and tooling decisions : evaluate and recommend the right approach for each use case, staying true to our vendor-agnostic DNA: AWS, Azure, Salesforce, a custom orchestration stack, and others, based on data gravity, integration, cost, governance, and time-to-value.
- Deliver clear trade-off analyses that executives and engineers both understand.
- Architect agentic & generative AI systems : design multi-agent workflows, RAG pipelines, tool/function calling, memory and state management, guardrails, and human-in-the-loop fallbacks.
- Build, hands-on : develop production-grade agents and automations with LangChain, LangGraph, Bedrock AgentCore, and other tools to integrate with enterprise systems (CRM, ERP) via APIs.
- Own quality and reliability : implement evaluation pipelines, observability, prompt/version management; optimize latency, cost, and accuracy of inference.
- Deliver PoCs, demos, and production solutions : move ideas from prototype to scaled deployment with proper CI/CD and AI and MLOps practices.
- Contribute to pre-sales and solutioning : shape solution offerings, support proposals, and bring market knowledge and technical credibility to client conversations.
- Lead and mentor : provide guidance to engineers and interns, define best practices, and help build and scale our AI practice.
- Stay ahead : keep pace with a fast-moving field (new models, frameworks, MCP, agent protocols) and bring well-judged ideas to clients and teams.
Requirements
- Degree in Computer Science, Engineering, Data Science, or related field, or equivalent professional experience.
- 5+ years in software/AI/data engineering, including hands-on experience shipping generative or agentic AI to production
- Strong Python and solid software-engineering fundamentals (APIs, microservices, version control, testing).
- Hands-on experience building AI agents / tool-using LLMs with an orchestration framework.
- Practical experience with AWS AI services , especially Amazon Bedrock (foundation models, agents, guardrails) and the broader AWS stack (Lambda, API Gateway, S3, IAM).
- Solid grasp of RAG , embeddings, chunking, hybrid/semantic search, reranking, evaluation, vector databases.
- Proven ability to evaluate platforms objectively and make architecture decisions — and justify them to both technical and business audiences.
- A consulting mindset: curiosity, ownership, structured communication, and a collaborative, teamwork-first attitude.
- Hands-on experience with Salesforce Agentforce and Data 360.
- Relevant certifications (e.g., AWS Certified AI/ML or Solutions Architect ; Salesforce Agentforce / Platform credentials a bonus).
- Industry domain knowledge (financial services, retail, supply chain, healthcare).
Benefits
- A stimulating environment where you will be able to surpass yourself and discover new horizons;
- A strong culture of innovation and entrepreneurship;
- Many occasions to celebrate your success : 5 @ 7, team activities, birthdays, breakfasts and other special events;
- Group insurance for you and your family members;
- RRSP and DPSP participation plan;
- Monthly Wellness Allowance;
- Reimbursement of telecommunication costs;
- Flexible work from home policy;
- 4 weeks of paid vacation;
- Language courses (French & English);
- Access to continuing education (in-house, conferences, events, courses, certifications, etc.);
- Development plan for each employee and coaching.
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