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Junior Software Engineer – Scientific Computing; C++

Job in Pine Bluff, Jefferson County, Arkansas, 71601, USA
Listing for: Axle
Full Time position
Listed on 2026-06-02
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Junior Software Engineer – Scientific Computing (C++)

Junior Software Engineer – Scientific Computing (C++)

Remote

(: )

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries.

Benefits We Offer
  • Paid Time Off and Paid Holidays
  • 401(k) match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)
Job Overview

Axle is seeking a Junior Software Engineer with a solid foundation in C++ and a genuine enthusiasm for LLM-based development workflows. This role sits at the intersection of traditional high-performance software engineering and the rapidly evolving landscape of AI-assisted coding tools and large language model (LLM) integration.

You will work as part of a collaborative, cross‑functional team building scalable software systems for compute‑intensive research environments. A key part of your day‑to‑day will involve leveraging LLM‑based tools—such as AI coding assistants, prompt‑driven code generation, and LLM‑integrated pipelines—to accelerate development and explore novel solutions to engineering challenges.

Key Responsibilities
  • Develop and maintain C++ software components for scientific and computational workloads, with a focus on correctness and maintainability.
  • Integrate and leverage LLM‑based tools (e.g., Git Hub Copilot, Claude, GPT‑4) throughout the development lifecycle—from code generation and review to documentation and debugging.
  • Build and experiment with LLM‑assisted pipelines for automating repetitive engineering tasks, code scaffolding, and developer productivity tooling.
  • Collaborate with senior engineers and researchers to prototype and evaluate LLM‑integrated solutions to complex software problems.
  • Contribute to testing, CI/CD workflows, and code documentation—using AI tools to maintain quality and delivery speed.
  • Stay current with the fast‑moving LLM tooling ecosystem and proactively share learnings with the team.

Note: Some projects involve image‑based data and scientific computing workflows. Prior expertise in these areas is not required; you will develop this knowledge with support from the team.

Required

Skills & Qualifications
  • 1–3 years of professional experience (or equivalent academic/research experience) in software development.
  • Working knowledge of C++, including comfort reading, debugging, and contributing to C++ codebases.
  • Demonstrated experience using LLM‑based development tools (e.g., Copilot, Cursor, Claude, ChatGPT) as part of a regular development workflow.
  • Familiarity with prompt engineering concepts and an understanding of how to effectively direct LLMs for code generation, review, or explanation tasks.
  • Working knowledge of Linux development environments.
  • Basic experience with Python for scripting, tooling, or working with LLM APIs (e.g., OpenAI, Anthropic).
  • Strong problem‑solving skills and eagerness to learn within a fast‑evolving technical landscape.
Preferred Qualifications
  • Experience building or integrating LLM‑powered features into applications or developer tooling (e.g., RAG pipelines, tool‑calling agents, code‑aware assistants).
  • Familiarity with LLM APIs (OpenAI, Anthropic, Hugging Face) or open‑source models (LLaMA, Mistral).
  • Understanding of modern C++ (17/20) idioms and experience with performance‑oriented development.
  • Exposure to scientific computing, numerical methods, or high‑performance computing concepts.
  • Experience with parallel computing concepts (multithreading, vectorization, OpenMP).
  • Familiarity with modern build systems (CMake, Bazel) and container technologies (Docker).
  • Interest in evaluating and benchmarking LLM output quality for engineering tasks.
What We Emphasize
  • Curiosity about LLM‑assisted development and a desire to push the frontier of AI‑augmented…
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