Easy Apply
Easy Apply
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
Top Skills
APIs
Cloud-Native Services
Container Orchestration
Embeddings
JavaScript
Llms
Python
Real-Time Audio
Stt
Tts
Typescript
Vector Dbs
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
As a Senior Software Engineer on the AI Platform, you'll develop scalable AI systems, focusing on backend services, workflows, and integrations, partnering with cross-functional teams.
Top Skills:
GoJavaLangchainOpenai SdkPython
Artificial Intelligence • Consumer Web • Digital Media • Information Technology • Social Impact • Software
The role involves shipping full-stack AI projects, designing experiments for AI features, and optimizing AI infrastructure while collaborating with teams.
Top Skills:
MySQLPostgresReactRuby On Rails
Logistics • Transportation • Travel
Design and build production-grade AI applications using LLM services, RAG, and agent orchestration. Develop backend systems and cloud deployments, implement evaluation/monitoring, and mentor engineers while defining reusable AI architecture patterns.
Top Skills:
Ai AgentsAntigravityAWSAzureAzure OpenaiClaudeClaude CodeCursorGCPGeminiGithub CopilotHugging FaceLlmsOpenaiRetrieval-Augmented Generation (Rag)Transformers
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
