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Ai Reliability Engineer Jobs in Connecticut (NOW HIRING)

Pho Prime, LLC

Sr. Performance Engineer

Shelton, CT · On-site

$108 - $132/hr

The role combines hands‑on performance engineering with reliability and resilience practices and ... policy‑compliant AI use. Qualifications * 5-7+ years in performance engineering or ...

NBCUniversal

Software Engineer

Stamford, CT · Hybrid

Working closely with our SRE team to ensure deployed systems are reliable, resilient, scalable, and ... Experience with AI tooling for code creation, reviews, testing and related software development ...

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Ai Reliability Engineer information

What is an AI reliability engineer?

AI Reliability Engineers are professionals responsible for ensuring that artificial intelligence systems function reliably, safely, and effectively over time. They work on monitoring AI models in production, identifying and mitigating potential failures, and improving the robustness of AI systems. Their tasks often include testing, validation, performance monitoring, and implementing best practices for maintaining AI infrastructure. By focusing on reliability, they help organizations deploy AI solutions that are dependable and trustworthy in real-world environments.

What are some common challenges AI reliability engineers face when ensuring model robustness in production environments?

Ai Reliability Engineers often encounter challenges such as monitoring AI model performance for drift or unexpected behavior, managing data quality issues, and implementing automated alerting systems for anomalies. In production, it's crucial to ensure that AI models operate consistently and remain reliable under varying conditions and data inputs. Collaborating closely with data scientists, software engineers, and DevOps teams is essential to address these challenges and to continuously improve model reliability and uptime.

What are the key skills and qualifications needed to thrive as an AI reliability engineer, and why are they important?

To thrive as an AI Reliability Engineer, you need a solid background in computer science or engineering, expertise in AI/ML concepts, and experience with software testing and reliability methodologies. Familiarity with tools like TensorFlow, PyTorch, CI/CD pipelines, and reliability testing frameworks, along with certifications in cloud platforms (e.g., AWS Certified Machine Learning), is highly valuable. Analytical thinking, problem-solving abilities, and strong collaboration skills set top performers apart in this role. These skills ensure robust, dependable AI systems that meet performance standards and maintain trust in critical applications.

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

AspectAi Reliability EngineerData Scientist
Required CredentialsBachelor's or master's in CS, engineering, or related; certifications in AI/MLBachelor's or master's in CS, statistics, or related; certifications in data analysis or ML
Work EnvironmentTech companies, AI-focused teams, engineering departmentsResearch labs, tech firms, analytics teams
Employer & Industry UsageAI product development, machine learning systems, reliability testingData analysis, predictive modeling, business insights

While both roles involve AI and ML, Ai Reliability Engineers focus on ensuring AI system robustness and uptime, whereas Data Scientists analyze data to generate insights and models. The roles often collaborate but serve different primary functions within AI projects.

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What job categories do people searching Ai Reliability Engineer jobs in Connecticut look for?

The top searched job categories for Ai Reliability Engineer jobs in Connecticut are:

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Cities in Connecticut with the most Ai Reliability Engineer job openings:

Ai Reliability Engineer jobs near you
Infographic showing various Ai Reliability Engineer job openings in Connecticut as of August 2026, with employment types broken down into 100% Full Time. Highlights an 49% In-person, and 51% Remote job distribution.

Senior Performance Engineer ID84179

AgileEngine

Shelton, CT • On-site, Remote

Full-time

Posted 15 days ago

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE
We are looking for a Senior Performance Engineer to own and lead an enterprise-wide Performance Engineering function as a horizontal shared service across a global QSR digital ecosystem including web, mobile, kiosk, POS, loyalty, and payments systems. You will design and execute load, stress, and endurance tests using JMeter, k6, or similar tools, integrate automated performance validation into Azure DevOps CI/CD pipelines, partner with SRE and DevOps teams on chaos engineering experiments, and leverage AI-assisted workflows for performance planning and results triage.

WHAT YOU WILL DO
- Own the enterprise Performance Engineering charter as a horizontal shared service, establishing engagement models and SDLC performance-readiness standards.
- Design, script, execute, and report performance tests (load, stress, endurance, scalability) across high-volume ordering, kiosk, POS, loyalty, and payment flows.
- Identify and resolve bottlenecks across application, database, messaging, and infrastructure layers using observability signals (e.g., Dynatrace).
- Embed automated performance validation into CI/CD pipelines (e.g., Azure DevOps) with baseline and threshold gating.
- Partner with SRE/DevOps teams to define reliability targets and run controlled chaos-engineering experiments (fault/latency injection, dependency degradation).
- Define performance-readiness criteria, provide evidence-based go/no-go release recommendations, and assist with production performance-incident resolution.
- Integrate AI-assisted workflows into performance planning, test-design acceleration, and results triage while maintaining AI-consumable artifacts and safety guardrails.

MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 4+ years of experience in performance engineering or non-functional testing at enterprise scale.
- Hands-on expertise with performance testing tools (e.g., JMeter, k6, LoadRunner, NeoLoad, or OctoPerf).
- Experience with enterprise observability and cloud monitoring platforms (e.g., Dynatrace).
- Demonstrated experience integrating automated performance validation into CI/CD pipelines (e.g., Azure DevOps).
- Scripting and automation proficiency in Java, JavaScript, or Python.
- Hands-on engineering experience in cloud environments (AWS or Azure).
- Hands-on experience using AI-assisted engineering tools, including reviewing and validating AI-generated output.
- Strong communication and stakeholder leadership skills with the ability to translate technical findings into clear business impact.
- Upper-intermediate English level.

NICE TO HAVES
- Direct experience partnering with SRE/DevOps practices on chaos engineering (fault/latency injection and dependency degradation testing).
- Prior experience supporting digital platforms within quick-service-restaurant (QSR), retail, or high-volume transactional ordering ecosystems.
- Experience maintaining AI-consumable artifacts (NFRs, workload models, baselines, thresholds) and defining AI guardrails.

PERKS AND BENEFITS
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location