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System Engineer Phd Jobs in Bloomfield, CT (NOW HIRING)

Deloitte

AI Engineer Consultant

Hartford, CT · Hybrid

Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML). * 2+ years of experience ... across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven ...

Henkel

Senior Project Engineer

Rocky Hill, CT · On-site +1

$100K - $130K/yr

Master's or PhD preferred * Excellent problem-solving skills with the ability to evaluate data ... Experience with FRP systems, specifically in the civil/structural market space for both seismic and ...

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All JobsSystem Engineer Phd JobsSystem Engineer Phd Jobs in Bloomfield, CT

System Engineer Phd information

See Bloomfield, CT salary details

$53.5K

$127.1K

$166.9K

How much do system engineer phd jobs pay per year?

As of Aug 19, 2026, the average yearly pay for system engineer phd in Bloomfield, CT is $127,128.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $156,900.00 per year, depending on experience, location, and employer.

What is a system engineer PhD?

System Engineer PhDs are professionals who have earned a doctoral degree (PhD) in systems engineering or a closely related field. They specialize in designing, analyzing, and managing complex systems across various industries, such as aerospace, defense, IT, and manufacturing. Their advanced education enables them to conduct research, develop innovative solutions, and lead multidisciplinary teams to tackle large-scale engineering challenges. System Engineer PhDs often work in academia, research institutions, or high-level industry roles, focusing on optimizing system processes and integration.

What are the key skills and qualifications needed to thrive as a system engineer PhD, and why are they important?

To thrive as a System Engineer PhD, you need advanced knowledge of systems engineering principles, research methodologies, and typically a doctorate in engineering or a related field. Familiarity with modeling and simulation tools (e.g., MATLAB, Simulink), systems engineering software (e.g., IBM DOORS), and relevant industry certifications are highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication skills help you lead complex projects and collaborate with multidisciplinary teams. These skills and qualifications are essential for driving innovation, ensuring robust system design, and successfully managing sophisticated engineering challenges.

What are common challenges system engineer PhDs face when transitioning from academia to industry roles?

System Engineer PhDs often encounter challenges when shifting from academic research to industry, such as adapting to faster project timelines and working within cross-functional teams. In industry, there is typically a greater emphasis on practical application and collaboration, rather than theoretical exploration. Adjusting to structured workflows and aligning technical solutions with business objectives are also key transitions. However, this environment offers opportunities to see the tangible impact of your work and to advance into senior technical or leadership roles.

What is the difference between System Engineer Phd vs Network Engineer?

AspectSystem Engineer PhdNetwork Engineer
Required CredentialsPhd in Engineering or related field, possibly with certifications like Cisco or CompTIAAssociate's or Bachelor's in Computer Science or related, with certifications like Cisco CCNA or CCNP
Work EnvironmentResearch labs, R&D departments, or advanced technical teams in tech companiesNetwork operations centers, IT departments, or telecommunications firms
Employer & Industry UsageResearch institutions, tech companies, or organizations requiring advanced system designTelecom providers, enterprise IT, or service providers

The main difference between a System Engineer Phd and a Network Engineer lies in their focus and qualifications. System Engineers with a Phd typically engage in advanced system design, research, and development, often in research or high-tech environments. Network Engineers focus on designing, implementing, and maintaining network infrastructure, usually with industry certifications. Both roles are essential in tech industries but serve different technical needs and expertise levels.

What can I do with a PhD in system engineer?

A PhD in system engineering prepares individuals for advanced roles in research, development, and systems design across industries such as aerospace, defense, technology, and manufacturing. Graduates often work as systems engineers, research scientists, or technical consultants, utilizing skills in systems analysis, modeling, and simulation, and may pursue careers in academia or industry innovation.

What are popular job titles related to System Engineer Phd jobs in Bloomfield, CT?

For System Engineer Phd jobs in Bloomfield, CT, the most frequently searched job titles are:

What job categories do people searching System Engineer Phd jobs in Bloomfield, CT look for?

The top searched job categories for System Engineer Phd jobs in Bloomfield, CT are:

What cities near Bloomfield, CT are hiring for System Engineer Phd jobs?

Cities near Bloomfield, CT with the most System Engineer Phd job openings:

System Engineer Phd jobs near you
Infographic showing various System Engineer Phd job openings in Bloomfield, CT as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $127,128 per year, or $61.1 per hour.

AI Engineer Consultant

Deloitte

Hartford, CT • Hybrid

Full-time

Re-posted 23 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

44th of 150 rated financial services

Job description

Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

Work you'll do

As an AI Engineer Consultant on the HC Forward team, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Qualifications

Required:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 2+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 2+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 2+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 2+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 2+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Must be legally authorized to work in the United states without the need for employer sponsorship, now or at any time in the future

Preferred:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 2+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 2+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 2+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 2+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 2+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 2+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 2+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 2+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $91,100 to $179,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.

For more information about Human Capital, visit our landing page at:https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY27  #HRSTFY27

Qualifications:

Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

Work you'll do

As an AI Engineer Consultant on the HC Forward team, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Qualifications

Required:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 2+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 2+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 2+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 2+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 2+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Must be legally authorized to work in the United states without the need for employer sponsorship, now or at any time in the future

Preferred:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 2+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 2+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 2+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 2+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 2+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 2+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 2+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 2+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $91,100 to $179,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.

For more information about Human Capital, visit our landing page at:https://www2....

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