Python Software Engineering Manager

EPAM Systems Inc; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

EPAM Systems Inc. seeks a Python Software Engineering Manager to lead an AI-powered financial assistant platform. You will guide a senior team and collaborate with technical stakeholders to ship chat, reporting, and customized interfaces into investment workflows.

You will design systems, own delivery end-to-end, and drive architecture decisions while adopting new languages and technologies as the stack evolves. Strong Python, React, AWS and AI tooling are essential.

Qualifications

• 8+ years hands-on software development in Python/React or similar.
• Willingness to learn Python quickly if not proficient.
• Hands-on with FastAPI, AWS, Kubernetes and Terraform.
• Autonomous, capable of end-to-end task delivery from analysis to design.
• Comfort in a startup-like environment with continuous learning.
• High standards for quality and reliability in software delivery.

Responsibilities

• Collaborate with a small, capable team in a startup-style setting.
• Partner directly with technical stakeholders without non-technical inputs.
• Translate high-level tasks into low-level requirements with edge-case coverage.
• Design systems and deliver production-grade implementations with autonomy.
• Influence product direction and architect decisions.
• Adopt new languages and tech as the stack evolves.
• Optimize AI apps for quality, latency, reliability, and cost.
• Review and test AI-generated code produced by coding agents.
• Monitor AI behavior in production and perform failure analysis.

Skills

Python

React (TS)

Autonomy

English (C1+)

AI-assisted coding

Software architecture

Quality engineering

Edge-case reasoning

Tools

FastAPI

AWS

Kubernetes

Terraform

Job description

We are looking for a Python Software Engineering Manager to build an AI-powered financial assistant platform. You will partner with a small senior team and technical stakeholders to ship chat, reporting, and bespoke interfaces into investment workflows.

Responsibilities

• Collaborate with a small, highly capable team of hands-on engineers in a startup-style environment with minimal formality
• Partner directly with sophisticated technical stakeholders without needing to interface with non-technical clients or users
• Elicit low-level requirements from high-level task definitions and account for edge cases before implementation
• Design systems and deliver production-grade implementations with strong autonomy and self-governance
• Influence product direction and contribute to architecture decisions
• Build and maintain systems using cutting-edge technology without legacy constraints
• Adopt new languages and technologies as the team evolves its stack
• Optimize AI applications across quality, latency, reliability, and cost
• Review, test, and validate AI-generated code produced through coding agents
• Monitor AI behavior in production and perform failure analysis and regression testing
• Maintain a high bar for quality, reliability, security, and maintainability across deliverables

Requirements

• Proven track record in software development with 8+ years of hands-on experience in Python, React (TS), or other programming languages
• Strong willingness and readiness to learn Python quickly if you are not yet proficient
• Hands-on experience with FastAPI or other Python frameworks, plus AWS, Kubernetes, and Terraform
• High autonomy and self-governance to take loosely defined tasks from requirements gathering through design and delivery
• Comfort working in a startup environment with continuous learning of new languages and technologies
• High standards for quality and reliability in software delivery
• Solid experience with FE work, including TS/JS and React/NextJS/Node
• Practical proficiency in AI-assisted programming methods and tools, including coding agents for code generation
• Background in AI evaluation and quality engineering, including automated evaluations, test datasets, regression testing, and failure analysis
• Understanding of AI security and production controls, including data privacy, access control, prompt-injection risks, guardrails, and auditability
• Ability to optimize AI applications across quality, latency, reliability, and cost
• Capability to learn and adopt new technologies rapidly as the AI ecosystem evolves
• Advanced proficiency in English (C1+)