Apex Systems is a leading Data and Digital Transformation professional services organization focused on providing solutions with real business value. We provide a customer-focused approach to building authentic partnerships with our clients with objective counsel from concept to deployment for a consistent voice through the dynamic IT environment.

What we look for:

We are seeking an AI Software Engineer to design, build, and deploy AI-powered tools and workflows that make analytics and engineering teams more effective. This is a hands-on software engineering role focused on delivering production-ready solutions—not research and not POCs only.

You will build AI agents, develop and maintain MCP (Model Context Protocol) servers, and create context-aware tooling that reduces manual effort and improves speed and quality across data/QA workflows. You’ll work closely with stakeholders to understand how teams operate today, identify high-impact automation opportunities, and ship reliable tools with clear adoption and measurable outcomes.

Responsibilities:

Applied AI & Process Optimization

Identify manual bottlenecks across reporting, tagging, and testing workflows and deliver automation that reduces cycle time.
Build AI agents that assist across the development lifecycle (requirements review, architecture review, coding, testing, debugging, deployment support).
Capture tribal knowledge into structured, searchable formats that improve onboarding and enable consistent AI assistance.

Agent Development & Automation

Automate repetitive tasks such as requirements gathering, data validation, job monitoring, and reporting support.
Build agents that interpret errors/logs, surface likely root causes, and recommend next actions or fixes.
Create reusable prompt templates, steering files, and workspace configurations to standardize AI behavior across teams.

Tool Integration (MCP & Engineering Platforms)

Develop and maintain MCP servers that connect AI tooling to internal systems and data context (schemas, metadata, business logic).
Integrate AI tooling with platforms such as Jira, Confluence, GitLab, and BI/reporting tools to reduce context switching and improve traceability.

Cost, Performance & Guardrails

Implement guardrails for AI-assisted query and automation workflows to avoid expensive or unbounded operations.
Build reliability patterns: observability hooks, validation checks, safe tool execution, and fail-safes.

Software Engineering Fundamentals

Build internal tools and services using TypeScript/React, Node.js, and Python.
Develop APIs and backend services that power agent workflows and integrations.
Write clean, tested, and documented code; contribute to engineering standards and maintainability.

Required Skills & Experience:

Bachelor’s degree in Computer Science or related field, or equivalent practical experience.
3+ years of software engineering experience delivering production applications (TypeScript/JavaScript, Python, or similar).
Hands-on experience building with LLMs, including prompt engineering, agent/tool-use patterns, and/or RAG systems.
Familiarity with MCP (Model Context Protocol) or similar agent-to-tool integration approaches.
Experience with AWS and building/deploying cloud-based services (e.g., Lambda, S3, DynamoDB, ECS).
Strong software debugging skills, including diagnosing issues across distributed services and automation workflows.
Ability to design thorough test cases and support reliability testing across tools and agents.
Strong written and verbal communication skills; ability to translate non-technical needs into working software.
Ability to manage your own work effectively and deliver iteratively.
English proficiency level C1 or higher is a requirement.

What we offer:

At Apex systems it is important to us that our employees feel comfortable and feel an important part of the organization. For this reason, we offer a superior benefits package such as: