Full Stack Software Engineer

Accenture Federal Services•Tampa, FL

About The Position

The Full Stack Software Engineer is responsible for delivering high quality, maintainable, and secure software across modern backend and frontend stacks. This role requires strong proficiency in contemporary programming languages, including Go and TypeScript/JavaScript (or equivalent technologies), with the ability to read, write, debug, and evaluate production grade code independently. Engineers in this role use AI coding assistants as a force multiplier while retaining full ownership of all resulting code. They must be able to decompose technical work, provide clear guidance to AI tools, and rigorously validate and revise generated output. Passive prompt and accept workflows are insufficient. A core responsibility of this role is code review and quality assurance. The engineer must be comfortable performing detailed, line by line review of both self authored and generated code, identifying defects, design issues, and unnecessary complexity. They should demonstrate practical knowledge of common software design patterns and architecture principles, including interfaces, dependency injection, factory and adapter/gateway patterns, and layered system design. They apply DRY, SOLID, and reuse first principles consistently. This role spans full stack development: backend services, data models, APIs, and modern web front ends. The engineer must maintain clear and stable contracts between client and server, ensuring well designed interactions across the stack. Work should reflect an understanding of cloud native fundamentals, including identity and access management, storage, databases, messaging, search, and containerized services. Solutions must be built against abstractions to remain portable across cloud and on premises environments. Strong data modeling skills are required, including experience with relational databases, schema creation, and migrations. The engineer must design for multi tenant security from the outset, understanding authentication versus authorization, isolation boundaries, least privilege access, and data protection considerations. The role also requires a commitment to continuous quality through unit, integration, and automated testing; use of linters, static analysis, and CI quality gates; and validation of changes in a running environment. Engineers are expected to adhere to established project standards in structure, naming, logging, error handling, and API design, introducing new patterns only when justified and reviewed. Effective problem solving is essential. The engineer must break large requests into verifiable increments, identify the correct system layer for each change, and communicate decisions clearly to peers and reviewers. Experience working in disconnected or constrained environments is important, including development without public internet access, use of private registries and pre approved dependencies, and deployment within isolated networks. Solutions must not rely on outbound SaaS, public container pulls, or live commercial AI services at runtime.

Requirements

2+ years of experience in Java.
Experience with Go Programming Language.
Experience with Cloud Infrastructure Architecture Design.
Experience with Full Stack Development.
Experience with AI Workflow Integration or AI Assisted Development.
Experience with establishing, and adhering to, security standards.
Active TS/SCI security clearance is required.

Nice To Haves

Security+
TypeScript
Experience working on multi-service or platform engineering teams.
Familiarity with defense, government, or other high assurance environments.
Experience with multi-cloud or air-gapped deployments.
Background in disconnected development using private artifact registries and cross-domain or multi-enclave release processes.

Responsibilities

Deliver high quality, maintainable, and secure software across modern backend and frontend stacks.
Use AI coding assistants as a force multiplier while retaining full ownership of all resulting code.
Decompose technical work, provide clear guidance to AI tools, and rigorously validate and revise generated output.
Perform detailed, line by line review of both self-authored and generated code, identifying defects, design issues, and unnecessary complexity.
Maintain clear and stable contracts between client and server, ensuring well-designed interactions across the stack.
Design for multi-tenant security from the outset, understanding authentication versus authorization, isolation boundaries, least privilege access, and data protection considerations.
Commit to continuous quality through unit, integration, and automated testing; use of linters, static analysis, and CI quality gates; and validation of changes in a running environment.
Adhere to established project standards in structure, naming, logging, error handling, and API design, introducing new patterns only when justified and reviewed.
Break large requests into verifiable increments, identify the correct system layer for each change, and communicate decisions clearly to peers and reviewers.
Develop solutions that do not rely on outbound SaaS, public container pulls, or live commercial AI services at runtime.