Build things that matter.
AuxDynamics is a senior engineering team — not a body shop. We hire people who want ownership over hard problems, not ticket queues. Remote-first, no layers of management, no politics. Just high-calibre engineers solving real problems for real clients.
We are looking for a Senior ML Engineer who has shipped production ML systems — not just notebooks. You will design, build, and maintain real-time inference pipelines, MLOps infrastructure, and ML-powered features for enterprise clients across fintech, healthcare, and retail verticals. This is a client-facing engineering role: you will own the technical relationship and architect solutions from first principles.
- Design and ship production ML pipelines — training, evaluation, deployment, monitoring
- Build MLOps infrastructure covering model registry, CI/CD, drift detection, and retraining
- Own the full technical delivery on 2–3 concurrent client engagements
- Architect RAG systems, LLM integrations, and autonomous agent workflows
- Contribute to internal tooling and AuxDynamics engineering standards
- 6+ years engineering with 3+ in production ML systems (not research)
- Deep Python, PyTorch or TensorFlow, and MLflow or similar MLOps tooling
- Hands-on experience with AWS SageMaker, Azure ML, or GCP Vertex AI
- Strong data engineering fundamentals — you own the full pipeline, not just the model
- Client communication skills — you can explain model tradeoffs to a non-technical CTO
We need a Solutions Architect who specializes in enterprise LLM deployments, multi-agent systems, and the non-obvious engineering decisions that separate reliable AI products from unreliable demos. You will work directly with enterprise clients as the primary technical authority on AI strategy, owning architecture from scoping through delivery.
- Lead architecture for complex AI engagements — RAG, agents, LLM fine-tuning, and evals
- Run discovery sessions with enterprise CTOs and present technical proposals
- Define AI system design patterns and contribute to internal IP and toolkits
- Mentor mid-level AI engineers and review architecture decisions across the team
- Stay current on frontier model developments and translate them into client opportunities
- 7+ years engineering with 3+ years in LLM/AI product architecture
- Deep familiarity with OpenAI, Anthropic, and open-source model ecosystems
- Production experience with vector databases, RAG pipelines, and agent frameworks
- Strong written communication — you produce architecture documents clients trust
- Comfortable leading client discovery sessions and technical presentations
You will architect and deliver production cloud infrastructure for enterprise clients — migrations, Kubernetes platforms, CI/CD pipelines, and IaC frameworks. You bring strong Terraform fundamentals, real multi-cloud experience, and the ability to own technical delivery on complex engagements without hand-holding.
- Architect and deliver cloud infrastructure on AWS and Azure for enterprise clients
- Build and maintain Kubernetes clusters, CI/CD pipelines, and IaC frameworks
- Lead cloud migration engagements — zero downtime, full documentation
- Implement FinOps practices and cost optimization strategies post-migration
- Own infrastructure security hardening and compliance alignment
- 5+ years in cloud infrastructure engineering with hands-on delivery ownership
- Expert-level Terraform — you write modules others use, not just scripts
- Production Kubernetes experience (AKS, EKS, or GKE) with Helm and GitOps
- AWS Solutions Architect or Azure equivalent certification preferred
- Solid Linux, networking, and security fundamentals — not just cloud console experience
You will build and maintain the CI/CD infrastructure, internal developer platforms, and deployment automation that powers AuxDynamics client deliveries. Strong GitHub Actions fundamentals, GitOps workflows, and a bias toward reducing manual toil across the engineering team.
- Build and maintain CI/CD pipelines for client and internal projects
- Develop internal developer platform tooling and deployment automation
- Implement GitOps workflows with ArgoCD or Flux across Kubernetes environments
- Support cloud infrastructure delivery alongside senior cloud engineers
- Drive observability standards — logging, tracing, and alerting frameworks
- 4+ years in DevOps or platform engineering with real delivery ownership
- Strong GitHub Actions, Jenkins, or GitLab CI experience
- Solid Docker and Kubernetes fundamentals with Helm chart management
- Terraform IaC experience — you can write and review modules independently
- Scripting proficiency — Bash and Python for automation and tooling
We need a Senior Security Engineer who has hands-on experience delivering cloud security programs — not just auditing them. You will lead SOC2, zero-trust, and compliance engagements for enterprise clients, design security architectures from first principles, and own the technical quality of every security deliverable that leaves under the AuxDynamics name.
- Lead SOC2, ISO 27001, HIPAA, and PCI-DSS compliance programs for clients
- Design zero-trust architectures and implement IAM frameworks on AWS and Azure
- Configure SIEM platforms, build detection rules, and run threat hunting exercises
- Conduct cloud security assessments and produce executive-grade findings reports
- Develop reusable security tooling, IaC modules, and compliance automation pipelines
- 6+ years in security engineering with direct client delivery experience
- Deep AWS or Azure security services — Security Hub, GuardDuty, Sentinel, Defender
- Hands-on SOC2 or ISO 27001 audit experience — you have been the owner, not the observer
- Strong IAM, network security, and zero-trust implementation fundamentals
- CISSP, CISM, AWS Security Specialty, or equivalent certification preferred
You will build full-stack SaaS platforms for enterprise clients — from multi-tenant architecture to performance-optimized frontends. You care deeply about system design, API quality, and shipping software that ages well. This is a delivery-focused role; you will own features end-to-end and take pride in the entire stack, not just your layer.
- Build full-stack SaaS platforms from architecture through deployment on client engagements
- Design multi-tenant data models, API layers, and frontend architecture
- Contribute to system design decisions and code review standards across the team
- Integrate third-party APIs, billing systems, and authentication providers
- Optimize frontend performance — Core Web Vitals, bundle size, lazy loading
- 5+ years full-stack with proven SaaS delivery ownership, not just contribution
- Strong Node.js or Python backend with REST and GraphQL API design experience
- React or Next.js frontend with performance optimization and accessibility awareness
- PostgreSQL or equivalent — you write and optimize complex queries yourself
- Comfort working directly with clients and presenting technical proposals
You will design and build the API and microservices layers that power client products and internal platforms. Strong fundamentals in distributed systems, API design, and database performance — with a bias toward correctness, observability, and code that doesn't surprise the next engineer who touches it.
- Design and build RESTful and event-driven microservices for client SaaS platforms
- Architect API gateways, service mesh configurations, and inter-service communication patterns
- Write performant, observable backend code with comprehensive test coverage
- Collaborate with cloud engineers on deployment and infrastructure requirements
- Participate in architecture reviews and contribute to engineering standards documentation
- 4+ years backend engineering with microservices delivery experience
- Strong in Python, Node.js, Go, or Java — depth in one, breadth across others
- PostgreSQL and Redis fundamentals — schema design, query optimization, caching patterns
- Message queue experience — Kafka, RabbitMQ, or AWS SQS in production
- Solid testing fundamentals — unit, integration, and contract tests are non-negotiable
You will architect and build enterprise data platforms — lakehouses, real-time streaming pipelines, and BI-ready transformation layers. You bring strong Snowflake or Databricks experience, dbt fluency, and a track record of turning fragmented data sources into reliable, governable analytical platforms that business teams actually trust.
- Architect and build lakehouse data platforms using Snowflake or Databricks
- Build real-time streaming pipelines with Apache Kafka and Spark Streaming
- Write and maintain dbt transformation models with full data quality test coverage
- Design data governance frameworks — cataloguing, lineage, and access controls
- Collaborate with BI engineers and data scientists to ensure model usability at the gold layer
- 5+ years in data engineering with end-to-end pipeline ownership
- Expert Snowflake or Databricks — medallion architecture, performance tuning, clustering
- dbt proficiency — macros, tests, incremental models, and CI/CD integration
- Production Apache Kafka experience — consumer groups, exactly-once, schema registry
- Python and SQL fluency — you write code others learn from, not code they fix
What working here actually looks like
No buzzwords, no perks designed to compensate for bad culture. Here is what we actually offer and how the team operates.
The entire team works remotely. No mandatory office days, no hybrid theatre. Async-first communication with structured weekly syncs and a shared Slack culture that actually works.
Every engineer owns their delivery end-to-end. No hand-offs, no siloed layers. You architect, build, deploy, and support — and you get full credit for outcomes.
You will work alongside engineers with 8–18 years of domain experience. Code reviews are substantive. Architecture discussions are real. You will grow faster here than anywhere else.
We pay in the top quartile for Canadian engineering compensation. All roles are salaried with performance bonuses. No negotiation games — the band in the posting is the real band.
Every engineer gets $2,500 CAD per year for conferences, certifications, courses, or books — no approval required, no justification needed. Spend it on what actually advances your craft.
Comprehensive health, dental, and vision coverage from your first day. No waiting period, no partial coverage during probation. Extended health, paramedical, and mental health included.
Core collaboration hours exist (10am–3pm MST), but the rest of your schedule is yours. Results and delivery quality are what matter — not when you logged in or how many Slack messages you sent.
Our clients bring us the problems their internal teams couldn't solve. You will work on ML systems in production, security programs at scale, and platforms serving millions of users. No CRUD apps.
Founded and operated from Calgary. We hire across Canada, pay in CAD, and operate with the straightforward, low-politics culture that defines the best Canadian engineering shops.
A hiring process that respects your time
Four steps. No surprise rounds, no take-home projects that take 8 hours. We move fast and communicate at every stage.
Send your resume and a 3-sentence explanation of why this role is a fit. We review every application personally — no ATS black holes. If we see a match, we respond within 48 hours.
48h responseA relaxed call with one of our engineering leads — not HR. We talk about your background, what you've built, what you're looking for, and answer your questions about the role and team honestly.
30 minutesA 90-minute technical discussion with two senior engineers focused on your specific domain. We discuss real problems you've solved, architecture decisions you've made, and how you think through tradeoffs. No whiteboard nonsense.
90 minutesIf it is a match on both sides, you receive a written offer within 24 hours of the final interview. No weeks of silence, no drawn-out negotiation. The number in the offer is fair from the start.
Offer within 24hWe hire for talent,
If you are an exceptional engineer in AI, cloud, security, or data and you don't see your exact role listed, reach out anyway. We regularly create positions for the right people. Send a short note and your resume to [email protected].