Job Title - AI Lead Developer (Generative AI / Agentic AI)
Client Name: Airbus
Office location: - Montreal - Hybrid (3 days/week onsite - Mirabel)
Duration: ASAP, Minimum 6 months
Possibility of Extension: Highly likely
Seniority: Senior / Lead (hands-on technical lead)
Description
Seniority: Senior / Lead (hands-on technical lead)
Language: English, Preferably Bilingual French & English
Role Objective
- Drive the design, development, and industrialization of Generative AI and Agentic AI solutions in a global, high-tech enterprise setting. This role owns the journey from PoC MVP production with enterprise-grade quality: security, scalability, reliability, observability, and governance. Candidate must be platform-agnostic; hands-on Google Cloud Platform experience is preferred. Familiarity with classical AI/ML for hybrid solutions is a strong advantage.
Key Responsibilities
- Technical Leadership & Architecture
o Define solution architecture for GenAI/agentic capabilities (RAG, tool/function calling, orchestration, guardrails).
o Make design decisions balancing quality, latency, cost, and compliance; produce lightweight architecture artifacts and decision logs.
- Hands-on Delivery (Prototype to Production)
o Build and deploy production-ready GenAI services/APIs (microservices) and reusable components (accelerators, templates, SDKs).
o Implement data ingestion + retrieval pipelines (chunking, embeddings, indexing) and integrate enterprise data sources.
o Establish evaluation approach (benchmarks, regression tests, golden datasets) and manage prompt/model versioning.
- LLMOps / Platform Enablement
o Implement CI/CD, automated testing gates, rollout strategies, monitoring/logging/tracing, and operational runbooks.
o Support incident/change workflows and ensure production readiness (SLOs, resiliency, cost controls).
- Security, Privacy & Responsible AI
o Implement controls for PII protection, access management, auditability, prompt-injection mitigation, safety filters, and governance alignment.
- Collaboration & Mentoring
o Partner with product, architecture, data, and security stakeholders; translate requirements into backlog and deliverables.
o Mentor engineers and align distributed/global teams on standards and delivery practices.
Required Skills & Experience
- 8+ years software engineering; 2+ years delivering GenAI/LLM solutions (hands-on).
- Demonstrated success taking at least one GenAI solution into production (not only PoCs).
- Strong coding in Python (and/or Java/Go/TypeScript) plus API/service engineering.
- Strong GenAI fundamentals: RAG, embeddings, prompt lifecycle, tool/function calling, agentic patterns, evaluation methods.
- Cloud-native engineering: containers, Kubernetes (or equivalent), CI/CD, IaC, observability.
- Ability to work onsite in Mirabel 3 days/week.
Preferred / Nice to Have
- Hands-on Google Cloud Platform (e.g., Vertex AI, BigQuery, Cloud Run/GKE, Pub/Sub, IAM/Secret Manager).
- Classical AI/ML exposure for hybrid systems (prediction + GenAI).
- Experience with vector DB / enterprise search and working in regulated/high-security environments.
Deliverables
- Production-grade GenAI/agentic service(s) with monitoring, alerting, runbooks, and support readiness.
- Reference architecture + reusable components and quality gates (evaluation, security, performance, cost).
- Secure integration with enterprise data and identity/access controls.
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