Principal Software Engineer

Principal Full Stack Engineer

Fidelity Wealth Group – Core Wealth Platform Technology is looking for a passionate Principal Full Stack Engineer to drive the development of software solutions for its business-critical Core Wealth Platform Operations. Our engineering team is innovative, diverse, passionate and dedicated, we work in a dynamic agile environment.

The Team

As a Principal Full Stack Developer, your primary role will be to understand and analyze emerging business requirements, translate it to a modern solution design and innovate for platform stability and resiliency. You will assist and work with architects and engineers to help deliver the solution into production. You will be expected to quickly gain understanding of the business needs and collaborate with the domain and solution architects to define and implement the next generation platform operations focused on AWS and AI solutions.

Key Responsibilities

· Design, develop, and maintain high-quality software components for core applications.

· Write high-quality, scalable, and maintainable code for both front-end (user interfaces) and back-end (servers, APIs, databases) components.

· Ensure the performance, security, and scalability of micro-service based applications.

· Collaborate with cross-functional teams to define, design, and ship new features.

· Participate in code and design reviews to maintain high development standards.

· Contribute to the continuous improvement of development practices, standards, and strategies.

· Implement and maintain CI/CD pipelines to ensure smooth and efficient software delivery.

· Write unit and integration tests to ensure software quality and reliability.

· Investigate and share innovative practices with team members.

Required Expertise

· Experience building RESTful backend services and modern front-end applications (React, Angular), with hands-on work in event-driven architectures and streaming platforms, and a solid understanding of microservices and cloud-native Kubernetes environments.

· Working knowledge of cloud environment configuration—including identity and access management, virtual networking, security controls, secrets and parameter management, and multi-account operational best practices—using AWS services such as IAM, VPC, Security Groups, and Parameter Store/Secrets Manager as examples.

· Experience with CI/CD pipelines using tools like Git, Jenkins, and Docker, along with familiarity with automated code-analysis and performance-insight tools (e.g., AWS DevGuru) to detect inefficiencies and operational issues.

· Strong understanding of modern observability platforms—covering distributed tracing, metrics, logs, dashboards, and alerting—using technologies such as OpenTelemetry, Datadog, and Amazon CloudWatch, with deep expertise in AWS metric strategies including custom metrics, metric filters, and performance-focused alert design.

· Strong database engineering background across relational and NoSQL systems, including complex query design, stored procedure analysis, performance tuning, security configuration, backup and recovery strategies, and cost-efficient scaling—using cloud database services such as AWS RDS, Aurora, and DynamoDB as examples.

· Experience applying Generative AI to accelerate development—code transformation, test generation, documentation automation, and intelligent troubleshooting. Ability to integrate AI services into backend systems and microservices with appropriate governance, monitoring, and cost controls.

· Proficiency with modern cloud-based object storage platforms—including bucket/container governance, lifecycle and retention policies, versioning, encryption, performance optimization, and replication strategies—using services such as Amazon S3 as examples.

· Experience with workflow-orchestration and state-management services for coordinating microservices, managing complex business processes, and handling long-running asynchronous operations—using platforms such as AWS Step Functions as examples.

· Foundational understanding of large language model (LLM) capabilities, including reasoning, multimodal inputs/outputs, and architectural integration patterns. Familiarity with LLM platforms such as OpenAI and Amazon Bedrock, including model selection, prompt flows, agent workflows, embeddings, and secure enterprise deployment.

Skills and Attributes

· Excellent analytical, problem-solving, communication, and organizational skills.

· Ability to prioritize and manage multiple tasks simultaneously.

· Strong team player with a collaborative and positive attitude.

· Ability to work independently under general direction.

· Commitment to quality and adherence to software engineering best practices

· Demonstrated ability to take ownership and responsibility of critical issues and conclude them to resolution.

The Value You Deliver

· Deliver high-quality, timely, cost-effective, and maintainable software solutions in an Agile environment.

· Contribute to test automation code and practices.

· Participate in engineering practices such as code and design reviews, and define source control, environment, and build and deployment strategies.

· Collaborate with product owners, technical leads, and architects to drive technical improvements.

· Share innovative practices and knowledge with team members.