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Emplia

Senior AI Engineer / AI Agent Lead

Montreal, QC, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Nov 1, 2026
Posting language: English
Posted: Oct 2, 2026

Original job description

Senior AI Engineer / AI Agent Lead

Emplia Inc.

Montréal, QC | Full-Time | Hybrid

Reports to: Head of Product

About Emplia

Emplia is building an AI-powered workforce support platform designed to transform how employees interact with HR, Time & Attendance, Payroll, and other enterprise workforce systems.

At the center of our platform is the Emplia Agent - a multilingual conversational AI that provides employees and managers with a single, intelligent entry point to workforce information, enterprise systems, and validated organizational knowledge.

Unlike a general-purpose chatbot, the Emplia Agent is designed for enterprise environments where accuracy, security, permissions, privacy, traceability, and controlled actions matter.

We are moving from Proof of Concept toward MVP and are looking for a senior AI engineerto take technical ownership of the Emplia Agent.

The Role

As Senior AI Engineer / AI Agent Lead, you will be responsible for the architecture, development, testing, and continuous improvement of the intelligence layer behind the Emplia Agent.

Reporting to the Head of Product, you will work closely with product, engineering, HR technology specialists, and external technology providers to translate product requirements into a reliable, secure, and scalable AI agent.

This is a highly hands-on position.

You will not simply configure an LLM or write prompts. You will own how the Agent reasons, retrieves information, interacts with enterprise systems, applies permissions and guardrails, uses tools, handles uncertainty, escalates cases, and delivers consistent multilingual experiences.

What You Will Own

You will take technical ownership of the Emplia Agent, including:

Design and development of the core conversational AI architecture
LLM integration, evaluation, and model-selection strategy
Retrieval-Augmented Generation (RAG) architecture
Vector and hybrid search
Knowledge retrieval, grounding, and source citation
Prompt, system-instruction, and context architecture
Agent skills and reusable AI capabilities
Intent recognition and request classification
AI tool use and function calling
Agent orchestration and workflow logic
Read versus transactional action routing
Explicit confirmation workflows for sensitive or transactional actions
Guardrails and controlled refusal behavior
Human escalation and exception handling
Hallucination prevention and factuality controls
Permission-aware retrieval and data access
Multilingual AI behavior
Speech-to-Text and Text-to-Speech integration
AI observability, tracing, and monitoring
AI evaluation and regression testing
Latency, reliability, and AI cost optimization
Privacy-aware handling of PII and conversational context
Technical documentation of AI architecture and design decisions

The Product Challenges You Will Help Solve

The Emplia Agent is being designed to operate across complex enterprise environments.

Some of the challenges you will work on include:

Providing answers exclusively from approved enterprise knowledge and authorized system data
Preventing unsupported or fabricated answers
Dynamically retrieving information from HR and workforce systems
Ensuring employees only access information they are authorized to see
Detecting conflicting data across enterprise systems
Knowing when the Agent should answer, ask a clarification question, execute an action, or escalate to a human
Creating safe confirmation workflows before transactional actions are executed
Supporting enterprise HR processes across multiple systems and clients
Maintaining strict tenant and data isolation
Delivering consistent experiences across text and voice
Supporting English, French, Spanish, and Finnish
Recognizing regional language variations, including Canadian French
Building a framework that allows new Agent skills and enterprise integrations to be added over time

What We're Looking For

Required

Strong professional software engineering experience
Hands-on experience developing production applications using Large Language Models
Strong Python development skills
Experience working with commercial LLM APIs or platforms such as OpenAI, Azure AI, Anthropic Claude, Google Gemini, or equivalent
Strong understanding of Retrieval-Augmented Generation (RAG)
Experience with vector databases, embeddings, semantic search, and/or hybrid search
Experience implementing LLM tool use / function calling
Experience building conversational AI, AI agents, or agentic workflows
Strong API and backend development skills
Experience combining LLM reasoning with deterministic application logic
Experience developing automated evaluation frameworks for AI applications
Understanding of authentication, authorization, and permission-aware systems
Understanding of AI hallucination, grounding, confidence, and failure modes
Experience handling sensitive or enterprise data
Experience with AI application logging, tracing, monitoring, and production troubleshooting
Strong problem-solving and software architecture skills

Strong Assets

Experience with one or more of the following would be particularly valuable:

Microsoft Azure
Microsoft Foundry / Azure AI
Azure OpenAI
Azure AI Search
Azure Speech
OpenAI APIs
PostgreSQL / pgvector
Semantic and hybrid retrieval
Enterprise search
Speech-to-Text
Text-to-Speech
Real-time conversational AI
Multilingual NLP
Enterprise SaaS
Multi-tenant applications
Enterprise integrations and APIs
HR technology or HRIS platforms
UKG
Workday
SAP SuccessFactors
Oracle HCM
Dayforce
ADP
Jira APIs
PII-sensitive applications
Enterprise security and compliance environments

Previous HR technology experience is valuable but not required. You will work closely with internal workforce technology and product experts.

What Success Looks Like

During your first months at Emplia, you will:

Take ownership of the existing Emplia Agent architecture and AI codebase
Establish a structured AI evaluation and regression-testing framework
Validate and optimize the LLM and retrieval architecture
Improve grounding, factuality, source citation, and refusal behavior
Improve tool-calling reliability and exception handling
Develop and refine Agent skills and guardrails
Establish AI observability and quality metrics
Validate multilingual performance
Help evolve voice capabilities
Support the transition from POC to pilot deployment
Lead the AI engineering workstream toward MVP
Establish engineering standards that allow the Emplia Agent to scale across additional clients, systems, languages, and workforce use cases

Who You Are

You enjoy solving problems that sit between AI research and real-world software engineering.

You understand that a production enterprise AI agent is much more than a prompt connected to an LLM.

You care about reliability, architecture, testing, security, and user experience.

You are comfortable experimenting with new AI technologies but equally comfortable deciding when deterministic software is safer and more appropriate than AI.

You are able to take ownership of a problem, propose a solution, build it, test it, measure it, and improve it.

And you want the opportunity to help shape an AI product from its early stages into a production enterprise platform.

Why Join Emplia

This is an opportunity to join Emplia at a pivotal stage as we move from Proof of Concept toward MVP and commercial deployment.

You will have significant influence over:

The architecture of the Emplia Agent
Our AI technology stack
How Agent skills are designed
Our AI engineering standards
How AI interacts safely with enterprise workforce systems
Our multilingual and voice strategy
The future AI engineering team

Rather than maintaining one small component of a mature platform, you will have the opportunity to take ownership of the intelligence behind the product and help build Emplia's AI engineering capability from the ground up.

Apply

If you're passionate about building reliable enterprise AI agents and want to take meaningful ownership of a product from POC through MVP and scale, we'd like to hear from you.

Send us your CV or LinkedIn profile and tell us about an AI application or agent you've built that you're particularly proud of.

Apply About employer

More about this job

Responsibilities

Own the architecture, development, evaluation, and ongoing improvement of the Emplia Agent, including its retrieval, orchestration, tool use, permissions, guardrails, and multilingual and voice capabilities. Lead the AI engineering workstream from proof of concept toward MVP by improving reliability, security, observability, and scalability across enterprise workforce systems.

Requirements

Requires strong professional software engineering experience, production experience with LLM applications, strong Python and backend/API skills, and hands-on expertise with RAG, search, tool calling, and conversational AI agents. Candidates should also understand evaluation, authorization, sensitive enterprise data, AI failure modes, and production monitoring; no specific education requirement is stated.

Skills

Python
Large Language Models
Retrieval-Augmented Generation
Vector Search
Hybrid Search
LLM Tool Use
AI Agent Development
Backend Development
API Development
AI Evaluation
Permission-Aware Systems
AI Observability
Multilingual NLP
Prompt Engineering
Enterprise Integrations
Software Architecture

Visa sponsorship

Not detected in the job text

Keywords

Python
Large Language Models
OpenAI
Azure AI
Anthropic Claude
Google Gemini
Retrieval-Augmented Generation
Vector Databases
Embeddings
Semantic Search
Hybrid Search
PostgreSQL
pgvector
Azure AI Search
Microsoft Foundry
Azure OpenAI
Azure Speech
Function Calling
AI Agents
Agentic Workflows
Prompt Engineering
Automated Evaluation
AI Observability
Speech-to-Text
Text-to-Speech
Multilingual NLP
Enterprise SaaS
Multi-Tenant Applications
HRIS
PII

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