Senior Software Engineer, IT Software Engineering

Ascensus•Lake Mary, FL

About The Position

As a Software Engineer in the Ascensus AI Program, you will help turn modern LLM capabilities into reliable, observable, production-grade software used by real business teams every day. This is a mid-level software engineering role for someone who is strong in core engineering fundamentals and excited to build practical AI-powered systems.

Requirements

3-7 years of professional software engineering experience.
Bachelor’s degree in Computer Science, Computer Information Systems, Business Information Systems, a related technical field, or equivalent practical experience.
Strong experience with one or more modern programming languages, such as: Python, JavaScript / TypeScript, SQL
Similar modern development platforms
Experience building production applications, APIs, integrations, backend services, workflow logic, or similar software components.
Familiarity with LLM-powered systems, such as: RAG, Chatbots, Agent workflows, Tool use, Prompt engineering, AI-enabled application development
Strong software engineering fundamentals, including: Clean code, Source control, Unit testing, CI/CD, Refactoring, Design patterns, Maintainability
Working experience with SQL for data inspection, analysis, troubleshooting, or integration.
Ability to read application logs, traces, and telemetry to investigate issues and identify root causes.
Strong problem-solving skills.
Clear communication skills with technical and non-technical audiences.
Comfort working in ambiguous, fast-moving environments.
Curiosity, ownership, and the ability to learn new technologies quickly.

Nice To Haves

Building or contributing to AI/LLM-based systems
RAG pipelines
Chatbots or conversational AI products
Agentic applications
Prompt strategies
Tool-calling workflows
Agent orchestration
Durable workflows or platforms such as Temporal
Model Context Protocol, function calling, or enterprise tool integrations
REST APIs, service-oriented architectures, or event-driven systems
Azure, Azure AI Foundry, Azure DevOps, or related Microsoft cloud tools
Salesforce or other enterprise platforms
Observability tools such as Langfuse, New Relic, OpenTelemetry, or similar platforms
AI-powered development tools such as Cursor, Claude Code, GitHub Copilot, or similar tools
Technical documentation, diagrams, decision records, or design notes
Working with quality engineers, SDETs, operations engineers, support teams, and product owners

Responsibilities

AI-powered applications and agents
Retrieval-augmented generation, or RAG, pipelines
Agent workflows and orchestration
Prompt strategies and tool integrations
Secure integrations with enterprise systems
Observability, testing, and production reliability
AI-assisted software development using tools such as Cursor, Claude Code, or similar platforms
Turn ambiguous business needs into simple, working software.
Use AI-assisted development tools to move faster without sacrificing quality.
Build AI systems that are observable, testable, and reliable enough for production use.
Care about retrieval quality, prompt behavior, tool accuracy, user experience, and measurable business outcomes.
Learn unfamiliar systems quickly.
Communicate clearly and ask good questions.
Make practical technical recommendations.
Take ownership from idea through design, implementation, deployment, monitoring, and improvement.
Help the team improve how it builds, tests, operates, and evolves enterprise AI software.