This is not a maintenance role. This is a reinvention role located in Huntsville, AL.

We are looking for a Principal Software Engineer who doesn’t just build systems—but reshapes how they are conceived, delivered, and trusted. Someone who pairs deep technical credibility with architectural vision, and who has the conviction to challenge legacy approaches when the mission demands more.

In this role, you will be a technical provocateur and lead engineer, driving the design and delivery of AI-enabled, agentic, and intelligent software platforms that dramatically accelerate modernization and outcomes. You’ll operate at the highest altitude—setting technical direction, evaluating emerging technologies, and prototyping what’s next—while still diving deep to turn ideas into production-grade reality.

This is a role for builders who bias toward action, who believe disruption can coexist with rigor, and who want to apply cutting-edge AI to the problems that matter most.

Why This Role Matters:

We are here to radically remake software systems that underpin the country’s most critical missions—aviation, healthcare, energy, and other safety-critical domains where failure is not an option. We are bringing agentic AI transformation not to trivial demos or disposable apps, but to the hardest, highest-stakes systems:

Systems with extreme safety, security, and resilience requirements
Systems constrained by regulation, legacy architecture, and operational risk
Systems where speed to outcome must increase without compromising trust
Our ambition is simple and audacious: move faster than ever before, while raising the bar on safety and reliability.

Key Responsibilities:

Technical Leadership & Architecture:

Provide Thought leadership in the future opportunities in AI and agentic-enabled tools, capabilities, and challenges
Serve as the architectural lead for AI- and agentic-enabled tooling, establishing patterns, reference implementations, and best practices.
Design scalable, secure, and resilient software systems that integrate LLMs, multi-agent workflows, code intelligence, and automation.
Own and drive the technical roadmap for next-generation software acceleration tools—including IDE extensions, code-analysis agents, refactoring engines, and developer-assistive AI.
Lead architecture reviews, evaluate new technologies, and set engineering standards for AI safety, quality, reliability, and observability.
Hands-On Engineering
Build high-quality software with modern languages and frameworks (e.g., Python, TypeScript, Go, Java).
Develop pipelines and services that enable AI reasoning, code analysis, static/dynamic analysis, and automated transformation of legacy systems.
Prototype early concepts rapidly and transition successful prototypes into robust, production systems.
Integrate AI/ML models (commercial, open-source, or custom) into enterprise environments and developer workflows.

AI & Agentic Systems Development:

Design and build agentic orchestration, tool-use interfaces, embeddings systems, context windows, and retrieval-augmented workflows.
Implement “human-in-the-loop” safety and review patterns.
Develop mechanisms for grounding, guardrailing, and evaluating AI performance and correctness.
Leverage AI to analyze, modernize, and refactor large, complex codebases (e.g., Java, .NET, COBOL, C++).

Collaboration & Influence:

Partner with product, UX, and platform teams to define features, user journeys, and developer experience goals.
Act as a technical mentor to senior and mid-level engineers; cultivate a culture of excellence and continuous learning.
Collaborate closely with research, data, and cybersecurity teams to ensure solutions are safe, secure, and aligned with mission needs.
Represent the engineering team in internal and external forums, contributing to thought leadership in AI and software engineering modernization.

Required Qualifications:

Bachelor's degree and 2+ years experience in software engineering, including significant experience at the senior/architect level. Additional experience may be considered in lieu of a degree.
Expertise in designing and building distributed systems, developer tools, or platform engineering products.
Hands-on experience implementing AI/ML systems or integrating large language models into production workflows.
Strong knowledge of agentic frameworks, orchestration tools, RAG, vector databases, API design, and microservices.
Deep understanding of software design patterns, CI/CD, Dev Sec Ops, and cloud-native architectures (AWS/Azure/GCP).
Strong coding proficiency in at least two modern languages (Python, Go, Java, C#, etc.).
Ability to drive technical strategy, influence cross-functional teams, and communicate complex ideas clearly.
Must be authorized to work in the U.S.
Ability to obtain and maintain a Secret security clearance.

Preferred Qualifications:

Experience modernizing legacy systems (e.g., mainframe, Java monoliths, .NET).
Background building developer experience (DevX) tools, IDE integrations, or code-intelligence systems.
Experience with AI/ML model fine-tuning, prompt engineering, or evaluation frameworks.
Familiarity with cybersecurity, secure-by-design principles, or government/missions systems
Prior role as a thought leader, principal engineer, architect, or technical founder.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

March 10, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $69,550.00 - $125,725.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.