Principal Investigator / Technical Research Lead

Resilient Core Systems, Inc.
Principal Investigator / Technical Research Lead
Artificial Intelligence & Government Systems
Resilient Core Systems, Inc. is developing advanced infrastructure and disaster-resilience technologies for government and public-sector environments.
RCS is seeking a senior Principal Investigator / Technical Research Lead to lead a proposed federally funded research initiative involving advanced artificial intelligence for disaster recovery and public-sector decision support.
We are looking for someone who understands not only how advanced AI systems are designed, trained, adapted, evaluated, validated, and improved, but also what is required to responsibly introduce AI into government and other high-consequence environments.
This position sits at the intersection of:
Advanced artificial intelligence and machine learning
Model development and evaluation
Multimodal AI and knowledge-grounded systems
AI governance and responsible AI
Human-in-the-loop decision systems
Model risk, uncertainty, explainability, and abstention
Data provenance and information integrity
Cybersecurity, privacy, and controlled access
Federal research and government technology environments
Scientific validation and reproducible R&D
This is not a general AI engineer, software-development manager, or product-management position.
We are seeking a research leader capable of establishing technically defensible research questions, developing experimental methodology, directing advanced AI research, establishing measurable success and failure criteria, and determining when an AI capability is—or is not—sufficiently validated for use in a high-consequence environment.
The underlying research requires expertise across applied machine learning, multimodal data engineering, distributed systems, human-factors validation, uncertainty, provenance, and governed AI operation.
Grant-Contingent Appointment
This position is being recruited in connection with a proposed federally funded research project.
The selected candidate may participate in proposal development and, where appropriate, may be identified as proposed Principal Investigator / Technical Research Lead.
Selection or participation in proposal activities does not constitute immediate paid employment.
The paid research appointment will begin only upon receipt of the applicable federal award, final project authorization, completion of RCS employment requirements, and satisfaction of all applicable program requirements.
Final designation as Principal Investigator will be subject to confirmation of applicable federal PI eligibility, employment, availability, and project requirements.
Who Should Apply
We are particularly interested in:
Current or former Principal Investigators, Co-PIs, senior research scientists, research directors, or technical R&D leaders
AI/ML researchers with demonstrated experience leading experimental research
Researchers experienced in training, adapting, evaluating, or validating advanced AI models
Researchers specializing in multimodal AI, generative AI, knowledge-grounded AI, retrieval systems, graph-based methods, or advanced machine learning
Researchers working in trustworthy AI, responsible AI, AI governance, or model-risk management
Researchers with experience designing AI systems where outputs inform decisions but do not independently exercise decision authority
Researchers experienced with government, defense, emergency management, critical infrastructure, healthcare, financial services, or another regulated/high-consequence environment
Researchers with experience in NSF, SBIR/STTR, federally sponsored R&D, university research, national laboratories, or comparable programs
Researchers with strong publication, patent, technical-report, or experimentally validated R&D records
What You’ll Do
Serve as the proposed Principal Investigator and technical research leader for an advanced AI research program.
Help finalize research questions, scientific hypotheses, technical objectives, experimental methodology, and feasibility criteria.
Lead research involving advanced artificial intelligence intended for eventual use in government and public-sector environments.
Guide model-development strategy, including training, adaptation, grounding, retrieval, evaluation, validation, and appropriate use of advanced AI architectures.
Establish rigorous comparison baselines rather than assuming a complex AI approach is automatically superior.
Develop benchmark datasets, ground-truth methodologies, evaluation protocols, failure scenarios, and reproducibility requirements.
Lead evaluation of AI behavior across incomplete, conflicting, uncertain, multimodal, and temporally changing information.
Establish quantitative methods for measuring model accuracy, reliability, calibration, uncertainty, provenance, traceability, latency, and operational usefulness.
Develop and evaluate strategies for hallucination/confabulation detection and mitigation.
Establish methods for confidence estimation, uncertainty escalation, and model abstention when evidence is insufficient.
Define acceptable and unacceptable AI behavior within government-facing workflows.
Establish deterministic human-review, escalation, and approval requirements for consequential outputs.
Work with cybersecurity, infrastructure, compliance, domain, and research personnel to ensure AI research remains scientifically rigorous and operationally appropriate.
Review technical claims and prevent unsupported representations of model capability, accuracy, safety, or readiness.
Support technical proposal development, research documentation, experimental plans, technical reports, and federal research deliverables.
Direct or coordinate specialized AI/ML researchers, engineers, data specialists, and validation personnel.
Contribute, where appropriate, to peer-reviewed research, conference materials, technical publications, and intellectual-property development.
The existing research plan calls for controlled experiments evaluating representation, multimodal evidence reconciliation, disrupted/offline operation, human-governed recommendations, and integrated performance under representative failure conditions.
AI Governance & Government Deployment Expertise
A major component of this position is understanding that technical model performance alone is not sufficient for government deployment.
The Principal Investigator should be capable of establishing a research and governance framework covering the full AI lifecycle, including:
Model and dataset documentation
Training and evaluation methodology
Model limitations and intended-use boundaries
Data quality and provenance
Human oversight
Explainability and source grounding
Confidence and uncertainty
Hallucination and failure analysis
Bias and performance variation
Model monitoring
Version control and change management
Reproducibility
Security and controlled access
Privacy and appropriate data handling
Auditability and traceability
Incident and failure response
Model rollback or withdrawal
Responsible deployment and use restrictions
The successful candidate should understand that an AI recommendation can be technically useful while still being inappropriate if it changes consequential government or recovery state without proper human authority. The underlying research therefore requires explicit separation between machine-generated recommendations and authorized human decisions.
Current AI Governance Awareness
We are looking for someone who actively follows the rapidly evolving AI environment—not someone whose knowledge stopped with an earlier generation of machine learning.
Candidates should demonstrate working familiarity with current developments in:
Generative AI and foundation-model research
Multimodal models
Retrieval-augmented and knowledge-grounded systems
AI agents and increasingly autonomous systems
Model evaluation and red-teaming
Hallucination and reliability research
Explainable and interpretable AI
Model uncertainty and calibration
Responsible AI and trustworthy AI
AI governance frameworks
Government AI acquisition and deployment considerations
Security and privacy implications of AI
Emerging federal standards, guidance, and compliance expectations
Model monitoring and lifecycle governance
The successful candidate will be expected to continuously evaluate new AI capabilities and emerging governance requirements and determine which developments are scientifically relevant to the RCS research program.
Technical Research Areas
Strong candidates should demonstrate substantial expertise across several of the following areas:
Artificial intelligence and

Work arrangement
Yes