At Intelliforce, we’re not just adopting AI—we’re redefining its role in operational environments. As a Senior Applied AI Engineer, you won’t be replicating the latest trends—you’ll be pioneering the next wave of real-world, mission-driven AI solutions. Embedded with elite cyber operations teams, you’ll engineer tools that automate the impossible, reimagine workflows, and bring high-stakes innovation directly to the front lines. This is where uptime matters, edge cases are the norm, and your ideas directly shape the future of national security.
Architecting and deploying production-grade AI systems purpose-built for operational cyber environments
Designing agent orchestration frameworks that intelligently coordinate models, tools, and tasks
Leading research sprints and prototyping sessions to explore novel AI applications
Developing and scaling MCP servers (or similar model-serving infrastructure) for secure, real-time access to AI models
Engineering advanced prompt strategies tailored to nuanced, high-risk cyber use cases
Building resilient integration layers that gracefully manage model behavior, tool dependencies, and system errors
Mentoring junior engineers while writing and reviewing high-quality production code
Making technical and architectural decisions that prioritize both innovation and mission reliability
Driving strategic discussions on the real capabilities and limits of AI in ops settings
Delivering proof-of-concepts that challenge norms and bring bold ideas to life
Establishing best practices for AI systems within classified and operationally constrained environments
Clearance: TS/SCI with Full Scope Polygraph
Citizenship: U.S. Citizen
Education & Experience:
Bachelor’s degree in a technical discipline + 12 years of engineering experience
OR 16 years of relevant experience with no degree requirement
Expert-level proficiency in Python, with 12+ years of software engineering experience
Demonstrated success deploying AI systems into production, beyond prototypes or demos
Deep understanding of AI architecture including agents, retrieval-augmented generation (RAG), function calling, and orchestration
Hands-on experience with MCP servers or other model-serving platforms
Proven success with prompt engineering in dynamic, real-world environments
Strong background in resilient distributed systems and fault-tolerant design
Comfortable with async workflows, graceful degradation, and failure-handling strategies
Sharp understanding of the capabilities and limitations of LLMs, APIs, and AI toolchains
Ability to rapidly prototype, iterate, and scale solutions responsibly
Strong instincts for debugging AI-specific issues, especially in non-deterministic environments
History of navigating and succeeding in ambiguous, greenfield problem spaces
Applied experience in cybersecurity, intelligence, or mission operations involving AI
Contributions to open-source AI projects, research papers, or major AI frameworks
Experience with fine-tuning, domain adaptation, or building domain-specific models
Knowledge of adversarial AI, model safety, or secure AI deployment strategies
Background in building developer platforms, SDKs, or internal AI tooling
Public speaking, technical blogs, or publications in applied AI or engineering strategy
Leadership in high-risk, ambiguous environments where innovation meets urgency
Active engagement in the AI/ML engineering community
Equal Opportunity Matters
Intelliforce-IT Solutions Group, LLC is proud to be an Equal Opportunity/Affirmative Action Employer. U.S. Citizenship is required for most positions.
Need accommodations during the application process? We’re happy to help. Reach out to us at [email protected] with your specific request.