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Remote Ai Data Engineer Jobs in Springfield, MA (NOW HIRING)

Director of Data Science

Hartford, CT · On-site +1

$153K - $229K/yr

Partner with Actuarial, Data Engineering, and other modeling organization teams to connect modeling ... Drive modernization through advanced modeling techniques, machine learning, and AI to enhance ...

Software Engineer

Hartford, CT · Remote

$72K - $130K/yr

If you reside near Hartford, CT , you'll enjoy the flexibility of a hybrid-remote position* as you ... Partner with product, data, and engineering teams to identify high-value AI use cases and translate ...

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Provide technical leadership across machine learning, statistical modeling, feature engineering ...

Partner with leadership to ensure financial data is audit-ready and decision-ready at all times ... Exposure to AI tools or automated accounting workflows Compensation & Benefits Notice The national ...

AVP, Software Engineering Lead

Hartford, CT · On-site +1

$255K/yr

This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office ... Define and lead the AI engineering strategy aligned to enterprise technology, Data & AI, and ...

AVP Data Science - GD05AE We're determined to make a difference and are proud to be an insurance ... This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office ...

Sales Director

Hartford, CT · Remote

$100K - $140K/yr

... remote work with travel for in-person client engagement on needed basis. ABOUT THE ORGANIZATION Arivonix - We are an Agentic AI Platform for Real-Time Enterprise Data Management and Monetization ...

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Showing results 1-20

Remote Ai Data Engineer information

See Springfield, MA salary details

$44.3K

$129.3K

$176.9K

How much do remote ai data engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for remote ai data engineer in Springfield, MA is $129,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $137,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Remote AI Data Engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What is a Remote AI Data Engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a Remote AI Data Engineer, and why are they important?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.
What are popular job titles related to Remote Ai Data Engineer jobs in Springfield, MA? For Remote Ai Data Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Remote Ai Data Engineer jobs in Springfield, MA look for? The top searched job categories for Remote Ai Data Engineer jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Remote Ai Data Engineer jobs? Cities near Springfield, MA with the most Remote Ai Data Engineer job openings:
Infographic showing various Remote Ai Data Engineer job openings in Springfield, MA as of July 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $129,263 per year, or $62.1 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Hartford, CT • Remote

$123K - $162K/yr

Full-time

Posted 15 hours ago

Posted today


Job description

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

AMC Health · Remote (US) · Full-time

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

Real-time voice AI

  • 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

LLM engineering

  • 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.

Work authorization (no exceptions)

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

Please submit both of the following:

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

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