Job Specifications
Software Guidance & Assistance, Inc., (SGA), is searching for an Sr Java Engineer for a CONTRACT assignment with one of our premier INSURANCE clients in CHARLOTTE, NC (Hybrid Schedule) .
We are looking for a Senior Java Developer who will serve as a dedicated engineering
efficiency champion across multiple application teams. Unlike typical feature developers, this role is singularly focused on identifying, building, and shipping improvements that raise the productivity, code quality, and operational maturity of the entire engineering organization—with a strong emphasis on leveraging AI tooling.
You will embed with different application teams, understand their codebases and business contexts rapidly, and deliver pull requests that introduce automation, reduce toil, improve CI/CD pipelines, and integrate AI-assisted development practices.
Responsibilities:
Cross-Team Engineering Efficiency
Rotate across multiple application teams to identify efficiency bottlenecks, technical
debt, and automation opportunities.
Deliver production-ready pull requests that improve build times, test coverage,
deployment reliability, and developer experience.
Establish reusable patterns, shared libraries, and internal tooling that all teams can
adopt.
AI-Powered Development Practices
Evaluate and integrate AI coding assistants (e.g., GitHub Copilot, custom LLM-based
tools) into the team's daily workflow.
Build internal AI-powered utilities such as automated code review bots, intelligent test
generators, documentation generators, and PR summarizers.
Champion AI-augmented development practices and train teams on effective prompt
engineering and AI-assisted coding techniques.
Identify high-ROI areas where AI can accelerate development cycles, reduce repetitive
work, or improve code quality.
CI/CD & DevOps Improvement
Optimize and extend existing CI/CD pipelines (build, test, deploy) for Spring Boot
microservices on AWS ECS.
Implement automated quality gates, security scanning, dependency vulnerability checks, and performance regression tests.
Reduce deployment cycle times and improve rollback capabilities across environments.
Codebase Health & Modernization
Refactor legacy patterns, remove dead code, and improve architectural consistency
across Java/Spring Boot applications.
Improve observability by enhancing logging, tracing, and monitoring instrumentation.
Standardize database query patterns, connection pooling, and PostgreSQL performance tuning.
Technology Stack
Layer Technologies
Backend Java 17+, Spring Boot, Spring Data JPA, Spring Security, REST APIs
Frontend Angular (TypeScript)
Database PostgreSQL
Cloud & Infra AWS (ECS, ECR, CloudWatch, S3, RDS, IAM, VPC)
CI/CD Jenkins / GitHub Actions / AWS CodePipeline (or equivalent)
Containerization Docker, AWS ECS (Fargate or EC2 launch type)
AI Tooling GitHub Copilot, LLM APIs, custom AI integrations
Required Skills:
10+ years of hands-on Java development with deep expertise in Spring Boot, Spring
Data, and RESTful API design.
Proven ability to quickly understand and navigate large, unfamiliar codebases and grasp business context rapidly.
Strong experience with PostgreSQL or any other relation or non-relation including query optimization, indexing strategies, and schema design.
Solid working knowledge of AWS services, specifically ECS (Fargate/EC2), ECR,
CloudWatch, RDS, S3, and IAM.
Hands-on experience designing, building, and optimizing CI/CD pipelines (Jenkins,
GitHub Actions, CodePipeline, or similar).
Proficiency with Docker and container orchestration on AWS ECS.
Familiarity with Angular front-end development (ability to read, review, and make
targeted improvements).
Strong Git workflow skills: branching strategies, code review, conflict resolution, and PR best practices.
Excellent problem-solving ability and a self-starter mentality—able to operate
independently with minimal direction.
Preferred Qualifications
Experience integrating AI/ML tools into developer workflows (Copilot, CodeWhisperer,
LLM APIs, custom AI bots).
Background in developer experience (DX) or platform engineering roles focused on
internal tooling.
Experience with infrastructure-as-code (Terraform, CloudFormation) and configuration
management.
Familiarity with observability stacks (Datadog, New Relic, ELK, or Prometheus/Grafana).
Contributions to open-source projects or internal developer tooling initiatives.
Knowledge of security best practices, OWASP guidelines, and automated security
scanning tools.
What Success Looks Like
Timeframe Expected Outcomes
First 30 Days Onboarded across primary applications; completed codebase audits;
identified top 10 efficiency improvement opportunities; first PRs merged.
60 Days Delivered measurable CI/CD improvements; introduced at least one AI powered tool or workflow adopted by a team; established efficiency backlog.
90 Days Demonstrated quantifiable productivity gains (e.g., reduced build times,
increased automate