Rapidly prototype and iterate AI-powered features (LLMs, embeddings, real-time audio, APIs), lead experiments from hypothesis to proof-of-concept, collaborate with product and engineering to translate prototypes into product-aligned solutions, and share learnings and artifacts to accelerate team innovation.
Parasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.
We move fast, stay close to our customers, and ship products that make a real difference for AI developers. This role is part of that mission.
About the RoleWe’re looking for a hungry, creative engineer who thrives in a high-trust, high-velocity environment. You’ll be the one taking bold ideas—from voice and real-time AI to new LLM-driven features—and turning them into working prototypes in days. You’ll operate inside our product and engineering organization, collaborating directly with the team to ensure what you build is not just exciting, but also aligns with our long-term architecture and customer needs.
This is an engineering role through and through, but with the freedom to explore, test, and build at startup speed.
Responsibilities- Rapidly prototype AI-powered workflows and tools, incorporating LLMs, embeddings, real-time audio/voice, API integrations, and prompt engineering
- Lead experimental build cycles from hypothesis to working proof-of-concept to actionable insights
- Collaborate closely with product and engineering to translate prototypes into viable product features
- Ensure alignment with platform architecture; seek guidance before integrating prototypes into production systems
- Navigate open-ended engineering problems with creative, experimental solutions
- Share learnings and code artifacts to accelerate team-wide innovation
- Proficiency in Python and/or JavaScript/TypeScript and ability to quickly learn new tools and frameworks
- Hands-on experience with AI systems including LLMs, API-based embeddings, vector DBs, and real-time pipelines (e.g., audio/STT-TTS)
- A bias toward action—you build, ship, iterate, and learn
- Demonstrated creativity: thinking in prototypes, not decks
- Strong communication and collaboration skills, particularly in technical cross-functional settings
- Past experience in startups, innovation labs, or “zero-to-one” product environments
- Familiarity working on AI infrastructure or backend systems, such as LLM pipelines, APIs, cloud-native services, and container orchestration
- Comfort navigating ambiguity and working across teams with minimal direction
- Experience contributing to open-source projects or public-facing engineering work
- Direct mentorship and visibility with our CEO, who is heavily involved in product and technical strategy
- Real ownership over high-leverage projects that shape product direction and customer experience
- A culture that marries engineering rigor with experimental agility
- The opportunity to influence the AI compute infrastructure shaping next-generation workloads
- Competitive compensation with meaningful equity, benefits, and a high-trust work environment
Similar Jobs
Kids + Family • Mobile
Design, build, and operate cloud backend services powering connected hardware: device connectivity, telemetry ingest, state management, and data pipelines. Own features end-to-end, lead medium projects, mentor juniors, collaborate with firmware/mobile/platform teams, apply AI-native engineering practices, and participate in on-call incident response and post-mortems to ensure scalable, secure, reliable systems.
Top Skills:
Aws EksAws LambdaBleClaude CodeCoapCursorDatadogDynamoDBGithub CopilotGrafanaKafkaKinesisMqttOpentelemetryPrometheusSqs
Consulting
Design, build, and deploy AI systems across the full lifecycle: data pipelines, model development (traditional ML and generative AI), agent-based applications, API integration, observability, and evaluation. Collaborate with architects and domain experts, support experimentation and production deployments, and assist with project coordination and stakeholder communications.
Top Skills:
Agent OrchestrationAgent Routing ProtocolsAutogenAWSAws SagemakerAzureAzure Machine LearningCi/CdCrewaiDockerEmbeddingsFastapiFlaskGoogle Ai/Ml ServicesLanggraphMcpMlopsOpenai ApisPrompt EngineeringPythonPyTorchScikit-LearnTensorFlowVector Databases
Information Technology • Real Estate
Design and build scalable .NET backend services and gRPC microservices; optimize data layers (SQL Server, MongoDB, Elasticsearch); implement cloud integrations on AWS and Azure; ship AI/ML features (LLMs, RAG, vector search, ranking, personalization) and operate MCP servers; contribute to CI/CD, observability, containerization, and production ML integrations impacting high-traffic consumer marketplaces.
Top Skills:
.Net 8+.Net Core.Net FrameworkAsp.Net Minimal ApisAWSAzureAzure Service BusC#Ci/CdDockerElasticsearchGa4GitGithub ActionsGrpcKafkaLangchainLlmsMediatrMlflowModel Context Protocol (Mcp)MongoDBNext.JsProtocol Buffers(Sql .Proto)PythonRagReactRedisSegmentSnsSQL ServerTypescriptVector Dbs
What you need to know about the Ottawa Tech Scene
The capital city of Canada and the nation's fourth-largest urban area, Ottawa has proven a rapidly growing global tech hub. With over 1,800 tech companies, many of which are leaders in their sectors, the city's tech talent now makes up more than 13 percent of its total workforce. This growth is driven not only by the big players like UL Solutions and Dropbox, but also by a thriving startup ecosystem, as new businesses emerge to follow in the footsteps of those that came before them.
