Python AI Engineer

EPAM Systems; Austin (TX); Remote; USD 130,000 - 145,000; Full time

Benefits offered by this job

Medical, Dental and Vision Insurance

Health Savings Account

Flexible Spending Accounts

Disability Insurance

Life and AD&D Insurance

Employee Assistance Program

LinkedIn learning solutions

401(k) Matching

Paid Time Off 15-25 days

Paid Holidays

Legal Plan and Identity Theft Protec

Accident Insurance

Employee Discounts

Pet Insurance

Employee Stock Purchase Program

Discretionary annual bonus

Discretionary Long-Term Incentive (LTI

Job summary

EPAM Systems, Inc. is seeking a Python AI Engineer to evolve our enterprise knowledge platform infrastructure. You will work on Confluence/GitHub ingestion pipelines, vector searches, and RAG-enabled services using Python and FastAPI.

You will design robust retrieval, grounding, and evaluation pipelines, build agent runtimes, and enhance observability with OpenTelemetry, Prometheus, and Grafana. Collaboration across product and engineering teams will be essential.

Qualifications

• 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.
• 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.

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.

Skills

Python experience

CLI tools Python/Golang/Rust

LangGraph LangChain pgvector

LLM evaluation frameworks

Docker Helm GitHub Actions Kubernetes

Embeddings and vector search

Metrics, tracing, dashboards

ETL pipelines

Reliability, cost, latency

Tools

Docker

Helm

GitHub Actions

Kubernetes

LangGraph

LangChain

pgvector

Job description

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.

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
• 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

• Medical, Dental and Vision Insurance (Subsidized)
• Health Savings Account
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Short-Term and Long-Term Disability (Company Provided)
• Life and AD&D Insurance (Company Provided)
• Employee Assistance Program
• Unlimited access to LinkedIn learning solutions
• Matched 401(k) Retirement Savings Plan
• Paid Time Off – the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)
• Paid Holidays - nine (9) total per year
• Legal Plan and Identity Theft Protection
• Accident Insurance
• Employee Discounts
• Pet Insurance
• Employee Stock Purchase Program
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program

This Remote Position Cannot be Performed in New York City.

This posting includes a good faith range of the salary EPAM would reasonably expect to pay the selected candidate. The range provided reflects base salary only. Individual compensation offers within the range are based on a variety of factors, including, but not limited to: geographic location, experience, credentials, education, training; the demand for the role; and overall business and labor market considerations. Most candidates are hired at a salary within the range disclosed. Salary range: $130,000 - $145,000. In addition, the details highlighted in this job posting above are a general description of all other expected benefits and compensation for the position.

In accordance with the LA County Fair Chance Ordinance, you may find a copy of the Notice containing a summary of the Ordinance’s key provisions here: Concept FCO Posting 8 27 24 (lacounty.gov)

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 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.