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/GitHub 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 OpenTelemetry, Prometheus/Grafana, Docker/Helm, and GitHub 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 LangGraph, LangChain, pgvector, and modern retrieval pipelines

Experience designing evaluation frameworks for LLM-backed systems, including regression detection and quality measurement

Strong experience with Docker, Helm, GitHub Actions, and Kubernetes-oriented workflows

Systems Understanding: Familiarity with the operational characteristics of embedding pipelines, vector search, and LLM-backed systems

Robust 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 LinkedIn learning solutions

EPAM Systems, Inc. is an equal opportunity 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 chance 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.

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