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Java Junior Jobs in Monson, MA (NOW HIRING)

The Hartford

Staff Software Engineer

Hartford, CT · Hybrid

$116K - $174K/yr

Mentor junior and mid-level engineers, providing technical guidance, code reviews, and fostering a ... Expertise in at least one modern programming language such as Java, Python, C#, or Go. * Strong ...

Judge Group, Inc.

Quality Assurance Analyst

Hartford, CT · On-site

$40 - $42/hr

Mentor junior team members and promote quality engineering best practices. Minimum Qualifications ... Java * Salesforce Testing * REST API Testing * SOAP Web Services * Postman * SQL * Mobile ...

Pwc

Senior Technical Product Owner

Hartford, CT

$127K - $168K/yr

You will also guide and mentor junior team members, fostering a collaborative environment that ... Contribute to scalable software solutions using languages such as Java, Python, and C++. Own ...

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Java Junior information

See Monson, MA salary details

$63K

$110.3K

$166.2K

How much do java junior jobs pay per year?

As of Aug 18, 2026, the average yearly pay for java junior in Monson, MA is $110,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,900.00 and $109,900.00 per year, depending on experience, location, and employer.

What is a Java Junior?

Java Junior developers are entry-level software engineers who specialize in programming using the Java language. They typically have a foundational understanding of Java syntax, object-oriented programming concepts, and basic software development practices. Java Juniors often assist with coding, debugging, and testing under the supervision of more experienced developers, while continuously learning and building their technical skills. Their responsibilities may also include maintaining existing applications and writing simple features as part of a development team.

What are the key skills and qualifications needed to thrive as a Java Junior, and why are they important?

To thrive as a Java Junior, you need a solid understanding of Java programming, object-oriented principles, and a relevant degree or coursework in computer science. Familiarity with development tools like Eclipse or IntelliJ IDEA, version control systems (such as Git), and basic knowledge of databases are typically expected. Strong problem-solving abilities, eagerness to learn, and good communication skills help juniors excel in collaborative and fast-paced environments. These skills enable efficient coding, effective teamwork, and smooth adaptation to evolving project requirements.

What are some typical challenges a Java Junior might face when starting out, and how can they overcome them?

As a Java Junior, you may encounter challenges like understanding complex codebases, adapting to agile development practices, and debugging unfamiliar issues. It's common to feel overwhelmed at first, but asking questions, participating in code reviews, and pairing with more experienced developers can accelerate your learning. Regularly practicing coding, studying documentation, and using collaboration tools will also help you quickly become a productive member of the team.

What is the difference between Java Junior vs Java Developer?

AspectJava JuniorJava Developer
Required Experience0-2 years2+ years
CertificationsOptional, entry-level certificationsOptional, advanced certifications
Work EnvironmentTraining, mentorship-focusedProject-driven, independent
ResponsibilitiesLearning, basic coding tasksDesign, develop, maintain Java applications

Java Junior roles are entry-level positions focused on learning and supporting Java projects, often requiring minimal experience. Java Developers have more experience, handle complex tasks, and contribute to project design and implementation. The transition from Java Junior to Java Developer involves gaining skills, experience, and certifications over time.

Java Junior jobs near you

AI Architect in Hartfort, CT 06155 and Charlotte, NC 28212 - Hybrid

Amicis Global

Hartford, CT • On-site

$80 - $90/hr

Contractor

Re-posted 28 days ago

Job description

ob Title: AI Architect
Location:  Hartfort, CT 06155 - Hybrid
Duration: 06 Months + Extensions
 
Role Overview:
The Hartford is seeking a highly skilled, hands-on AI Architect to support the Enterprise Technology Architecture (ETA) organization. This role will be responsible for leading the design, governance, and implementation of AI-centric technology architectures across a hybrid infrastructure landscape, including AWS, Google Cloud Platform (GCP), and on premises data centers.
The AI Architect will play a critical role in enabling the responsible and secure adoption of Generative AI (GenAI) technologies, establishing architectural standards, and driving the implementation of multiple internal-facing GenAI use cases. This role requires a strong blend of strategic architectural background and hands-on technical execution.
Key Responsibilities:
Architecture & Strategy
  • Design and develop Agentic AI solutions leveraging Google ADK, LangGraph/Langchain  and Agent Engine on Google Cloud Platform (GCP).
  • Deliver innovative AI capabilities that enhance business processes and customer experiences through GenAI and Agentic AI frameworks.
  • Ensure AI solutions align with enterprise technology strategy and meet scalability, security, and compliance requirements.
  • Drive adoption of GenAI and Agentic AI frameworks across business units.
  • Conduct proof-of-concepts (POCs) for emerging AI technologies and frameworks.
  • Collaborate with enterprise architects to ensure AI solutions align with technology strategy and reference architectures.
  • Stay current with AI trends, frameworks, and best practices to propose innovative solutions.
  • Cloud Security (AWS & GCP)
  • Architect and implement secure cloud solutions leveraging native services and third-party tools.
  • Define and enforce cloud security posture management (CSPM), identity and access management (IAM), and encryption strategies.
  • Collaborate with DevOps and cloud engineering teams to embed security into CI/CD pipelines and infrastructure-as-code.
  • Datacenter & Hybrid Security
  • Ensure secure integration between cloud platforms and on-prem data centers, including network segmentation, VPNs, and secure data flows.
  • Oversee security controls for legacy systems and their modernization paths.
  • GenAI Security Enablement
  • Define security and governance frameworks for GenAI platforms and use cases.
  • Ensure responsible AI practices including data privacy, model integrity, and ethical AI usage.
  • Collaborate with AI/ML teams to secure model training, inference, and deployment pipelines.
  • Governance & Collaboration
  • Serve as a key member of the Enterprise Technology & Solution Governance
  • Partner with business, IT, and risk stakeholders to align security architecture with enterprise goals.
  • Provide technical guidance and mentorship to junior engineers and architects on AI development practices.
Required Qualifications:
Experience:
  • 10-12 years in Software Engineering, with at least 2+ years in GenAI and Agentic AI development.
  • Project Delivery:
  • Must have delivered at least one GenAI or Agentic AI project end-to-end.
Technical Expertise:
  • Strong proficiency in Google ADK, LangGraph/Langchain, Agent Engine, and Vertex AI.
  • Hands-on experience with GCP services: Cloud Run, ECS, Vertex AI Search Engine, IAM, and networking.
  • Solid understanding of GenAI patterns, LLM fine-tuning, and prompt engineering.
Programming Skills:
  • Python, Java, or similar languages for AI development.
Cloud Certifications:
  • GCP Professional Machine Learning Engineer or GCP Professional Cloud Architect preferred.
Education:
  • Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
Soft Skills:
  • Strong problem-solving, communication, and collaboration skills.

Key Competencies:
  • Strategic and analytical thinking
  • Successfully integrated AI agents into business or technical workflows for automation and enhanced decision-making.
  • Improved operational efficiency and customer experience through AI-driven innovation.
  • Established reusable AI patterns and best practices for enterprise adoption.
  • Strong communication and stakeholder engagement
  • Proactive and solution-oriented mindse 
 
 
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