We are hiring a **Python AI Engineer** to operate and evolve the infrastructure behind an enterprise knowledge base platform as it transitions from a Confluence-focused RAG chatbot into a broader, agentic knowledge system.

Today, our platform supports Confluence/Git

Hub ingestion → chunking → pgvector → RAG retrieval → FastAPI serving.

In our next growth phase, we are expanding toward hybrid retrieval (vector + sparse + graph), multi-source ingestion, robust evaluation pipelines, agent infrastructure, and shared chat platform primitives.

If you are passionate about building scalable, reliable, and production-grade AI infrastructure rather than just chasing demo behavior, we want to hear from you.

Req.#(phone hidden) **Responsibilities** Architect and implement robust backend services using Python 3.11, FastAPI, Pydantic, SQLAlchemy async, and asyncpg Design trade-offs around retrieval quality, latency, cost, safety, and operational simplicity Build production-grade agent runtime capabilities, including memory boundaries, tool sandboxing, permissions, and budget controls Improve answer grounding, failure analysis, and citation enforcement for enterprise-grade dependability Create comprehensive observability and operational feedback loops using Open

Telemetry, Prometheus/Grafana, Docker/Helm, and Git

Hub Actions Ingestion infrastructure across current and future content sources Full-stack observability across application, pipeline, database, and model-serving behavior Cost, latency, throughput, and failure-mode management for AI-heavy workloads Release workflows that validate AI behavior changes,



not just code compilation Partner closely with product and engineering teams to support multiple conversational surfaces through a unified knowledge platform **Requirements** Strong, hands-on Python experience in platform, automation, or infrastructure-heavy environments Experience building CLI tools using Python, Golang, or Rust Hands-on experience with Lang

Graph, Lang

Chain, pgvector, and modern retrieval pipelines Experience designing evaluation frameworks for LLM-backed systems, including regression detection and quality measurement Strong experience with Docker, Helm, Git

Hub Actions, and Kubernetes-oriented workflows Systems Understanding: Familiarity with the operational characteristics of embedding pipelines, vector search, and LLM-backed systems Strong skills across metrics, tracing, dashboards, alerting, and log analysis Experience with ingestion, ETL, or content-processing pipelines at scale An innate ability to think in terms of reliability, cost, latency, throughput, and disaster recovery **Nice to have** Experience with Qdrant, Neo4j, or other vector/graph infrastructure Prior experience supporting RAG, search, evaluation, or agent platforms Background in enterprise or highly regulated environments Familiarity with enterprise tooling such as Vault, Splunk, Artifactory,



or ECR Comfort leveraging AI-assisted engineering workflows in day-to-day work **We offer** Extended Healthcare with Prescription Drugs, Dental and Vision, and Healthcare Spending Account (Company Paid) Life and AD&D; Insurance (Company Paid) Employee Assistance Program (Company Paid) Telehealth (Company Paid) Short-term Disability (Company Paid) Long-Term Disability Paid Time Off (including vacation and sick days) Registered Retirement Savings Plan (RRSP) with Company match Maternity/Parental/Adoption Leave Top-up Employee Stock Purchase Program Critical Illness Insurance Employee Discounts Unlimited access to Linked

In learning solutions EPAM Systems, Inc. is an equal chance employer.

We recognize the value of diversity and inclusion in creating success for our customers, business partners, shareholders, employees and communities.

We are committed to recruiting, hiring, developing and promoting employees without discrimination.

As a global employer, this commitment includes complying with all laws in the countries in which we operate.

Nevertheless, we believe equal employment practices should not be limited to what the law requires.

Equal opportunity and inclusion are essential to motivate, empower and recognize the best in everyone.

At EPAM, employment actions are based on individual qualifications, without regard to race, color, religion, creed, gender, pregnancy status, sexual orientation, gender identity, gender expression, marital or familial status, national origin, ancestry, genetics, age, disability status, veteran status, citizenship status when otherwise legally able to work, or any other characteristic protected by law.

📌 Python AI Engineer (Canada)
🏢 EPAM Systems
📍 Canada