Senior Applied AI Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• The Flex platform assists clients in establishing a thorough compliance program by utilizing technology to foster a culture of safety and ensure a productive work environment.

• This platform integrates features specifically designed to meet our clients' business requirements, such as audits and inspections, incident management, adaptable training, and comprehensive reporting and insights.

• Oversee the design, development, and expansion of the Agentic AI Platform, evolving the established Enterprise EHS/ESG SaaS system (Flex) into an innovative, AI-native intelligence and action system.

• Proficient in crafting complex state-machine routing code in Python, implementing auto-scaling serverless pipelines on AWS, configuring secure vector search engines, and developing dynamic widget-rendering APIs for the frontend.

• Developed and deployed enterprise-grade AI products to production, addressing real-world challenges such as multi-tenancy, PII redaction, token costs, latency, and model hallucination.

⛳️ Requirements

• SaaS Product Experience: A minimum of 5 years in software development, including at least 2 years dedicated to building and scaling production-grade AI features within a cloud-native SaaS environment.

• Educational Background: A robust academic foundation in Computer Science, Data Science, Software Engineering, or a highly quantitative discipline (e.g., Mathematics, Physics, Statistics). A Bachelor's degree in Computer Science, Engineering, or a related technical field is preferred.

• Technical Stack: Must possess hands-on, production experience with the following technologies:

• - Languages: Python (Expert/Senior level), TypeScript/JavaScript (Strongly Preferred).

• - AI Frameworks: LangGraph, LangChain, Vercel AI SDK, or equivalent.

• - AWS Infrastructure: Amazon Bedrock, ECS Fargate, S3, SQS, EventBridge, KMS, AWS Lambda, Amazon Comprehend, IAM.

• - Databases & Search: PostgreSQL / pgVector, Amazon OpenSearch Serverless, SQLAlchemy.

• - Data Processing: Pandas, NumPy, PyPDF, Layout-OCR engines.

• - API & Protocols: REST, Server-Sent Events (SSE), Webhooks, and Model Context Protocol (MCP).

• Hands-on AWS Background: Extensive experience in designing secure AWS architectures utilizing Least Privilege IAM execution roles, SigV4 API signing, and KMS envelope encryption.

• RAG at Scale: Proven experience in indexing and searching datasets comprising millions of document chunks, with a solid understanding of Direct Bulk Indexing APIs.

• System and Security Architecture: A strong grasp of authentication patterns (OAuth 2.0, JWT pass-through) and methods for logically isolating data in multi-tenant shared databases.

• Clean Code Advocate: Proven capability to produce clean, unit-tested, and well-documented Python code, employing self-correction loops and graceful degradation patterns to manage model latency and API rate-limiting constraints.

• Collaboration & Agile: Excellent communication and collaboration skills, thriving in an agile, team-oriented environment.

🏝️ Benefits

• Medical

• Dental

• Vision

• Flexible Spending Accounts

• PTO

• Paid and Floating Holidays

• 401k with Company match and immediate vesting

• Company-funded Life Insurance

• Employee Assistance Programs

• No-cost Mental Health Benefits