Senior AI Engineer / AI Agent Lead

Emplia; Montreal; On-site; CAD 110,000 - 170,000; Full time

Job summary

Emplia is building an AI-powered workforce support platform in Montreal, seeking a Senior AI Engineer to own the Emplia Agent's architecture, AI codebase, and evaluation framework. You will shape how the agent reasons, retrieves data, and interacts with enterprise systems at scale.

You will collaborate with product, engineering, HR tech specialists, and external providers to deliver a secure, multilingual, and reliable MVP as we move from PoC to production deployment.

Qualifications

• Strong professional software engineering experience.
• Experience with commercial LLM APIs or platforms (OpenAI, Azure AI, Anthropic, Gemini, etc.).
• Strong understanding of Retrieval-Augmented Generation (RAG).
• Experience with vector databases, embeddings, semantic/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 logging, tracing, monitoring, and production troubleshooting.
• Strong problem-solving and software architecture skills.

Responsibilities

• Take ownership of the Emplia Agent architecture and AI codebase.
• Lead design and development of core conversational AI architecture.
• Oversee LLM integration, evaluation, and model-selection strategy.
• Shape Retrieval-Augmented Generation and vector/hybrid search.
• Define knowledge retrieval, grounding, and source citation.
• Develop prompts, system-instructions, and context architecture.
• Build reusable AI capabilities and agent skills.
• Implement permission-aware data access and tool use.
• Define agent orchestration and workflow logic.
• Establish evaluation frameworks and AI observability.

Skills

Software engineering

LLM APIs

RAG

Vector databases

LLM tool use

Conversational AI

API/backend development

Deterministic logic

AI evaluation frameworks

Auth/permissions

AI safety

Data handling

Observability/tracing

Architecture skills

Tools

OpenAI APIs

Semantic retrieval

Speech-to-Text

Text-to-Speech

Enterprise integrations

HR tech platforms

Job description

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 engineer to 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
• 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 elevate 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
• 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:

• OpenAI APIs
• Semantic and hybrid retrieval
• Speech-to-Text
• Text-to-Speech
• Real-time conversational AI
• Enterprise integrations and APIs
• HR technology or HRIS platforms
• UKG
• Workday
• SAP SuccessFactors
• Oracle HCM
• Dayforce
• ADP
• 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
• 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
• How Agent skills are designed
• 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.