This position requires the eligibility to obtain a security clearance. Non-US citizens may not be eligible to obtain a security clearance. The Defense Industrial Security Clearance Office (DISCO), an agency of the Department of Defense, handles and adjudicates the security clearance process. More information about Security Clearances can be found on the US Department of State government website here: https://www.state.gov/security-clearances 

Accelint is a mission-driven technology company focused on strengthening national security and supporting critical industries. We build the technologies that help operators and organizations see what’s happening, make faster and better decisions, take action with confidence, and stay ready for what comes next. Our work includes advanced sensors, autonomous systems, mission command and control software, AI-enabled training and simulation, and tools that improve logistics, maintenance, and overall readiness.  

For nearly 30 years we have supported military and civilian agencies across the Department of Defense, U.S. allies and partners, and essential industries. When you join Accelint, your work directly contributes to protecting national security and strengthening the systems our society depends on.  

We are looking for a Senior AI Quality Engineer who will focus on ensuring these AI-powered, agentic applications are reliable, observable, and safe to operate in mission-critical environments. You will design and integrate testing guardrails directly into agentic workflows, validate orchestration logic, and build custom evaluation and test harnesses tailored to how these systems actually behave, rather than relying on off-the-shelf QA tools that don't fit the problem space. 

In this role, you will help define how quality is measured, enforced, and continuously evaluated across these systems, from individual agents to end-to-end workflows. You'll work closely with AI engineers, program teams, and infrastructure to embed reliability, security, and evaluation signals into the fabric of the system as it's being built. 

The ideal candidate understands agentic system design, has strong instincts for failure modes in AI-driven workflows, and is comfortable building bespoke testing frameworks, simulators, and evaluation pipelines to ensure these applications can succeed in real operational contexts. 

Role & Responsibilities 

• Hands-on delivery: Participate across the AI solution lifecycle from requirements and design through development, testing, and deployment by writing code, building validation systems, reviewing pull requests, and delivering working AI quality capabilities in an iterative, agile environment. 
• Scenario-driven validation: Build and maintain systems that exercise agentic workflows against realistic scenarios, edge cases, and failure conditions, using custom harnesses and guardrail-style validations, to validate end-to-end behavior and orchestration. 
• Integration hardening: Define contracts, validation, and explicit failure behavior at integration points so agentic workflows degrade safely when dependencies misbehave. 
• Reusable quality components: Create shared libraries, reference harnesses, and validation utilities that teams can reuse to accelerate adoption of AI quality practices. 
• Quality by design: Architect agentic systems so correctness, safety, and expected behavior are enforced by design rather than validated after the fact. 
• Design-time risk reduction: Participate in solution design to identify likely failure patterns in agentic systems and influence architecture and constraints before implementation. 
• AI quality evaluation: Define and implement cost-conscious evaluation strategies for AI-enabled systems, including data quality validation, model relevancy, hallucination detection, failure analysis, and ongoing measurement of AI-driven behavior. 
• Mission-aligned evaluation: Work with cross-functional program teams, including engineering, infrastructure, security, and delivery stakeholders, to translate customer and mission needs into concrete evaluation criteria and success conditions. 
• Delivery collaboration: Communicate estimates, progress, and technical tradeoffs clearly to development leads and product owners, and work alongside other engineers to share knowledge, improve practices, and raise the overall bar for AI engineering quality. 

Required Experience: 

• Strong engineering foundation: 5+ years of professional software engineering experience. 
• Custom validation and evaluation systems: Demonstrated experience building bespoke validation, evaluation, or testing frameworks for complex systems, using or expanding tools such as Playwright, pytest, k6, Guardrails AI, or similar frameworks. 
• Data contracts and validation: Data validation, schema enforcement, and contract testing experience in distributed or service-oriented architectures. 
• Quality-focused engineering: Experience treating quality, reliability, and correctness as core design concerns, including building automation or validation systems that meaningfully influenced how software was designed, tested, and released. 
• Risk reduction and release confidence: Experience defining, interpreting, and acting on quality signals to assess system readiness, guide release decisions, and reduce risk in complex software systems. 
• AI systems: Hands-on experience designing, building, and operating AI-powered systems, including agentic workflows or orchestrated LLM-based applications. 
• Cloud-native delivery: Solid understanding of Amazon Web Services and its native AI/ML services.  
• CI/CD and iterative delivery: Practical experience integrating automation into CI/CD pipelines and delivering software in an iterative, agile environment. 
• Operational and security awareness: Working knowledge of security best practices relevant to regulated or mission-critical contexts. 
• Collaborative engineering: Proven ability to work effectively with cross-functional teams, communicate technical tradeoffs, and deliver outcomes in environments with multiple stakeholders. 
• Eligibility requirements: Must be a U.S. Citizen and able to obtain and maintain a U.S. Security Clearance. 

Preferred Experience: 

• Experience designing and operating visual regression and performance testing approaches for complex systems, including defining meaningful baselines, detecting regressions, and using results to inform release decisions. 
• Comfort working in a TypeScript/JavaScript and/or Python-based stack, including modern frameworks (e.g., React, Next.js) across frontend, backend, or tooling codebases. 
• Familiarity with custom LLM integrations, LLM evaluation techniques, prompt engineering, and approaches for assessing non-deterministic or probabilistic system behavior. 
• Exposure to monitoring or observability tooling (e.g., Datadog, Prometheus/Grafana) to support debugging or validation of complex systems. 
• Working knowledge of security, privacy, and data protection considerations specific to AI-powered systems. 
• Experience documenting system architecture and design decisions clearly for technical and non-technical audiences. 
• Background in building or operating software in regulated, mission, or government contexts, including DoD environments, test and evaluation processes (e.g., DT&E, OT&E), or compliance frameworks such as FedRAMP or CMMC. Experience supporting Air Force programs is a plus. 
• Ability and willingness to travel within the US as needed. 
• Active U.S. Security Clearance (or prior clearance). 

Clearance Requirements 

Some positions will require access to U.S. National Security information.  Positions that require this access will be required to receive and maintain a U.S. government personnel security clearance (PCL).  In order to qualify for this position, the candidate must be a US Citizen and either currently possess this National Security eligibility or be able to complete the investigation application process with a favorable determination and maintain that eligibility throughout their employment. To learn more about the security clearance process please access this link.  

EEOC & Know Your Rights 

Accelint companies are Equal Opportunity Employers. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, status as a protected veteran or any other status protected by applicable federal, state, and local law. We ensure that all employment decisions, including hiring, promotion, compensation, and other terms and conditions of employment, are based on merit, qualifications, and business needs. For more information about your rights, please review the "Know Your Rights" poster from the Equal Employment Opportunity Commission (EEOC). Know your Rights: English Spanish 

Pay Scales & Benefits 

The listed pay scale reflects the broad, minimum to maximum, pay scale for this position for the location for which it has been posted and is not a guarantee of compensation or salary. Other compensation considerations may include, but are not limited to, job responsibilities, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, or other applicable factors. 

Benefits include… 

• Paid Time Off 

• Paid Company Holidays 

• Medical, Dental & Vision Insurance 

• Optional HSA and FSA 

• Base and Voluntary Life Insurance 

• Short Term & Long-Term Disability Insurance 

• 401k Matching 

• Employee Assistance Program