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Internal Tools Engineer Jobs in Springfield, IL (NOW HIRING)

Hansoninc

Mechanical Engineer

Springfield, IL

$100K - $145K/yr

Utilize computer-aided design (CAD) software and simulation tools to model and simulate HVAC and ... internal and external stakeholders. * Provide high-level cost estimates, utilizing industry ...

Farnsworth Group

Plumbing Project Engineer

Springfield, IL · Hybrid

$99K - $149K/yr

Serve as a technical resource for clients, project teams, and internal staff throughout all phases ... Proficiency with Revit and other industry-standard design and coordination tools. * Ability to ...

Farnsworth Group

Plumbing Project Engineer

Springfield, IL · On-site

$99K - $149K/yr

Serve as a technical resource for clients, project teams, and internal staff throughout all phases ... Proficiency with Revit and other industry-standard design and coordination tools. * Ability to ...

Hansoninc

Structural Bridge Engineer

Springfield, IL · On-site

$105K - $135K/yr

Perform complex engineering calculations and utilize software tools for analysis and design ... Strong relationship-building skills with internal and external stakeholders. * Interest in varied ...

Stellantis

Product Quality Engineer

Springfield, IL

$71K - $92K/yr

Collaborate and lead internal and external resources to achieve project/program timing. * Lead ... tools. Our Benefits - Designed with You in Mind Comprehensive Health & Well-being Coverage From ...

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Stellantis

Product Quality Engineer

Springfield, IL · On-site

$71K - $92K/yr

Collaborate and lead internal and external resources to achieve project/program timing. * Lead ... tools. Our Benefits - Designed with You in Mind Comprehensive Health & Well-being Coverage From ...

New

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Showing results 1-20

All JobsInternal Tools Engineer JobsInternal Tools Engineer Jobs in Springfield, IL

Internal Tools Engineer information

How does an internal tools engineer typically collaborate with other departments within a company?

Internal Tools Engineers frequently work closely with teams such as product management, customer support, operations, and engineering to identify pain points and streamline workflows. They gather requirements through regular meetings, prioritize feature requests, and provide technical support for the tools they build and maintain. This cross-functional collaboration is essential for ensuring that internal solutions are both effective and user-friendly, allowing departments to operate more efficiently and focus on their core objectives.

What is the difference between Internal Tools Engineer vs Software Engineer?

AspectInternal Tools EngineerSoftware Engineer
CredentialsBachelor's in CS or related field, sometimes specialized certificationsBachelor's in CS or related field, often similar certifications
Work EnvironmentFocus on building and maintaining internal tools, dashboards, automationDevelops a wide range of applications, including customer-facing products
Industry UsageCommon in tech companies, startups, and large enterprisesUniversal across all tech sectors and industries
Search IntentLooking for roles focused on internal tools and automationSeeking general software development roles

Internal Tools Engineers specialize in creating and maintaining tools that improve internal workflows, whereas Software Engineers develop a broader range of applications, including customer-facing products. Both roles require similar technical skills and often overlap, but their focus areas differ significantly.

What does an internal tools engineer do?

An Internal Tools Engineer designs, builds, and maintains software tools and systems that help other employees within a company work more efficiently. These tools can range from automation scripts and dashboards to complex internal applications used across departments. The primary goal is to streamline workflows, reduce repetitive tasks, and improve productivity for teams like engineering, operations, support, and more. Internal Tools Engineers collaborate closely with stakeholders to understand their needs and create technical solutions that solve real business problems.

What are the key skills and qualifications needed to thrive as an internal tools engineer?

To thrive as an Internal Tools Engineer, you need strong programming skills (commonly in Python, JavaScript, or Java), experience with software development lifecycle, and a degree in computer science or a related field. Familiarity with internal platforms, automation tools, version control systems like Git, and CI/CD pipelines is often required. Excellent problem-solving, collaboration, and communication skills help you understand user needs and work effectively across teams. These competencies are crucial for developing efficient, user-friendly internal solutions that boost organizational productivity and streamline workflows.
What job categories do people searching Internal Tools Engineer jobs in Springfield, IL look for? The top searched job categories for Internal Tools Engineer jobs in Springfield, IL are:
What cities near Springfield, IL are hiring for Internal Tools Engineer jobs? Cities near Springfield, IL with the most Internal Tools Engineer job openings:
Internal Tools Engineer jobs near you

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Springfield, IL • On-site

$150 - $210/hr

Other

Posted 24 days ago

Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems) The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real‑time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you’ll work across
  • Streaming, low‑latency speech‑to‑speech systems built on modern LLMs
  • Telephony and real‑time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency‑sensitive path, where p99 matters and a stall is something a caller hears
  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi‑model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM‑as‑judge and automated agent‑tests‑agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure
Traditional (non‑LLM) machine learning
  • End‑to‑end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real‑world data; calibration and explainability for non‑technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines
Cloud and infrastructure
  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least‑privilege access, strict data‑handling discipline
  • Observability and telemetry‑driven debugging, tracing a production issue from a metric anomaly to root cause
Plus

Occasional full‑stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you’ll actually do
  • Ship and debug code on a live, real‑time voice pipeline where latency and correctness are user‑facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch‑analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor
Must‑haves
  • 7+ years building and operating production backend systems, with strong general‑purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands‑on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data
Nice‑to‑haves
  • Real‑time media or telephony experience
  • Front‑end / full‑stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)
How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply
  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.

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