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Solidity Remote Jobs in Connecticut (NOW HIRING)

Sr Software Development Engineer

Greenwich, CT · On-site +1

$137K - $181K/yr

... 2 remote) U.S. residents only; work must be performed within the United States. Experience / Qualifications * 10+ years of software development experience with strong hands-on coding ...

Sr Software Development Engineer

Greenwich, CT · On-site +1

$137K - $181K/yr

... 2 remote) U.S. residents only; work must be performed within the United States. Experience / Qualifications * 10+ years of software development experience with strong hands-on coding ...

Showing results 21-25

Solidity Remote information

See Connecticut salary details

$29.6K

$145.1K

$206.2K

How much do solidity remote jobs pay per year?

As of Aug 8, 2026, the average yearly pay for solidity remote in Connecticut is $145,069.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,428.00 and $173,121.00 per year, depending on experience, location, and employer.

What does a Solidity Remote do daily?

As a remote Solidity developer, your daily tasks generally include designing, coding, and testing smart contracts, performing code reviews, and staying updated on the latest blockchain protocols. You will frequently participate in team meetings, contribute to project discussions via collaboration tools like Slack or GitHub, and provide support to frontend developers integrating smart contracts with decentralized apps. Effective communication across time zones and strong documentation skills are essential for working efficiently in a remote, collaborative environment. Over time, you may have opportunities to take on greater responsibilities, such as leading contract audits or mentoring new developers, supporting long-term career growth within the blockchain space.

What skills and qualifications are needed for a Solidity Remote?

To thrive as a Solidity Remote developer, you need expertise in Solidity programming, smart contract architecture, and blockchain fundamentals, often supported by a degree in computer science or related experience. Familiarity with tools like Remix, Truffle, Hardhat, and version control systems such as Git, as well as certifications in blockchain or Ethereum development, is highly regarded. Strong self-motivation, problem-solving capabilities, and effective remote communication skills are critical for excelling in distributed teams. These competencies ensure secure, efficient contract development and seamless collaboration in the fast-paced decentralized technology sector.

What is a Solidity Remote?

A Solidity Remote job is a position where a developer works remotely to build and maintain smart contracts using Solidity, the programming language for Ethereum and other blockchain platforms. These roles typically involve writing and testing decentralized applications (dApps), auditing smart contracts for security vulnerabilities, and collaborating with blockchain teams. Remote Solidity developers can work for startups, enterprises, or decentralized autonomous organizations (DAOs) from anywhere in the world.

What are the most commonly searched types of Solidity jobs in Connecticut? The most popular types of Solidity jobs in Connecticut are:
What job categories do people searching Solidity Remote jobs in Connecticut look for? The top searched job categories for Solidity Remote jobs in Connecticut are:
What cities in Connecticut are hiring for Solidity Remote jobs? Cities in Connecticut with the most Solidity Remote job openings:

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Hartford, CT • Remote

$123K - $162K/yr

Full-time

Posted 24 days ago


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.