Senior Software Engineer

Ascensus is the leading independent technology and service platform powering savings plans across America, providing products and expertise that help nearly 16 million people save for a better today and tomorrow. Position Summary 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. Job Functions, Essential Duties and 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 We are looking for engineers who Move quickly Take ownership Learn fast Communicate clearly Care about quality Build secure, maintainable software Are excited to work in a fast‑moving AI environment You do not need to be an expert in every part of the AI stack on day one, but you should be curious, technically strong, and motivated to grow. Experience, Skills, Knowledge Requirements Required Qualifications 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, or 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, and 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. Preferred Qualifications 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. What Success Looks Like 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. #J-18808-Ljbffr