Senior Software Engineer - AI (Applied AI)

Location: Remote in Quebec, Canada

Company

hirify.global is a web technology company serving millions of customers through brands including Bluehost, HostGator, Domain.com, Network Solutions, Register.com, and Web.com.

What you will do

• Build production AI experiences including conversational agents, business and website creation tools, knowledge and FAQ agents, content experiences, domain discovery, and intelligent automation.
• Design and implement AI services with Python, FastAPI, asynchronous workers, PostgreSQL, Redis, queues, model APIs, and external tools.
• Build tool-calling agents, multi-step workflows, event-driven systems, and integrations with internal APIs, MCP tools, business systems, and knowledge sources.
• Develop RAG pipelines covering ingestion, chunking, embeddings, retrieval, reranking, metadata filtering, context construction, and citations.
• Create evaluation pipelines and diagnose hallucinations, retrieval failures, incorrect tool usage, agent loops, latency issues, provider failures, and inference costs.
• Own production quality across APIs, workflows, data, queues, model integrations, observability, testing, security, and support.

Requirements

• 5+ years of professional software engineering experience with production backend, distributed, or cloud-based systems.
• Production experience with Applied AI, LLM, RAG, NLP, or agent-based applications.
• Advanced Python skills, including FastAPI, asynchronous programming, Pydantic, SQLAlchemy or SQLModel, and production API development.
• Strong backend and distributed systems fundamentals, including REST APIs, concurrency, background processing, caching, reliability, and production debugging.
• Production experience with RabbitMQ, Kafka, Azure Service Bus, or equivalent messaging platforms, plus strong PostgreSQL and data modeling skills.
• Experience integrating LLM APIs, building tool-calling or agent workflows, using AI coding agents, and delivering measurable RAG quality and latency outcomes.

Nice to have

• Experience with Semantic Kernel, Microsoft Agent Framework, LangGraph, PydanticAI, MCP tools and servers, or model gateways such as LiteLLM.
• Experience with Docker, CI/CD, automated testing, observability, distributed tracing, OpenTelemetry, Langfuse, Azure AI Search, pgvector, Chroma, Kubernetes, Azure, or OCI.
• Knowledge of prompting, structured outputs, context management, model routing, retries, fallbacks, rate limits, streaming responses, grounding, hallucination mitigation, prompt injection risks, and agent guardrails.
• Experience building high-scale customer-facing AI products, open-weight model inference, AI safety controls, or automated agent evaluation systems.

Culture & Benefits

• Work independently from ambiguous customer and product goals through production delivery.
• Choose practical, measurable solutions rather than using agents or LLMs by default.
• Use AI coding agents to increase engineering velocity while maintaining architecture quality, testing discipline, security, and maintainability.
• Measure quality, latency, reliability, safety, and cost in production.