Principal Forward Deployed Engineer – AI & Developer Platform

JobgetherAI developer platforms

Remote position based in Ontario, Canada.Full-TimePrincipal

SalaryCompetitive annual base salary: CAD $115,600 to $185,000. Annual performance bonus: Eligibility for a discretionary annual bonus, subject to applicable plan terms. Equity compensation: Opportunity to receive a competitive new-hire equity grant and additional annual equity awards, subject to relevant plan documents and award agreements.

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Job Details

Experience: At least 17 years of total professional experience in technical software roles, including 10 or more years in software engineering and at least five years driving developer experience, API design, or AI platform architecture at scale.
Required Skills: PythonKubernetesGogRPCLangChain

Requirements

Have at least 17 years of total professional experience in technical software roles, including 10 or more years in software engineering.
Have at least five years driving developer experience, API design, or AI platform architecture at scale.
Demonstrate technical leadership with C-suite stakeholders while remaining hands-on with developers, platform engineers, and systems teams.
Bring advanced knowledge of RESTful API design, gRPC, OpenAPI specifications, API gateways, and enterprise integration patterns.
Have deep understanding of Kubernetes internals, custom controllers, CRDs, operator patterns, and Cluster API (CAPI).
Have experience with GitOps, continuous delivery pipelines, infrastructure-as-code automation, and developer self-service.
Bring practical experience building or supporting production LLM and generative AI application stacks, including frameworks and inference engines such as LangChain, LlamaIndex, Haystack, Semantic Kernel, Ray, vLLM, SGLang, and Triton Inference Server.
Be familiar with vector databases and search technologies such as Milvus, Qdrant, Pinecone, pgvector, and Weaviate, plus streaming and caching technologies such as Kafka, Redis, Pulsar, Spark, and Flink.
Have experience integrating virtualized GPU workloads and technologies such as NVIDIA vGPU, MIG, and GPUDirect RDMA.
Have advanced Go, Python, and TypeScript/Node.js skills for systems development, API microservices, custom controllers, and AI workflow integration.
Have experience with enterprise Kubernetes distributions and managed services such as Amazon EKS, Google GKE, Azure AKS, OpenShift, and Rancher, and understand application networking and storage abstractions.
A bachelor's degree in Computer Science, Software Engineering, or a related technical discipline is preferred; equivalent relevant professional experience may be considered.

Responsibilities

Serve as the technical bridge between enterprise application developers, platform engineering teams, product managers, and senior technology leaders.
Design and standardize REST, gRPC, and GraphQL APIs, Kubernetes CRDs, and SDKs.
Establish developer workflows, continuous delivery pipelines, GitOps practices, and self-service developer portals using tools such as Argo CD and Flux.
Build command-line interfaces, testing frameworks, and automation tools for Kubernetes and cloud infrastructure platforms.
Architect production infrastructure for LLM inference, agent-based applications, and RAG pipelines on GPU-accelerated environments.
Develop scalable architectures for distributed AI workloads and integrate vector databases, search systems, streaming technologies, and caching layers.
Develop production-quality software in Go, Python, and TypeScript, including platform operators, custom controllers, API services, and AI integration components.
Translate customer challenges and field experience into reusable engineering solutions, product requirements, and roadmap recommendations.
Mentor engineers and forward deployed engineering colleagues and collaborate with product and engineering leadership on platform strategy.

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