Basic information
Job Name:
Applied AI Engineer
Location:
Washington, DC
Line of Business:
Global Technology & Solutions
Job Function:
Investor Services
Date:
Tuesday, June 2, 2026
Applied AI Engineer
Software Engineering, Data Science
Washington, USA
USD 150k-170k / year
Posted on Jun 11, 2026
Position Summary
The Applied AI Engineer role is designed for a technically strong, hands-on engineer who thrives at the intersection of full-stack software engineering, AI workflow development, and production reliability.
In this role, the Engineer will help turn frontier AI capabilities into trusted production systems by building platform patterns, workflows, data contracts, evals, observability, permissions, and governance that let the firm deploy AI safely at scale.
In-Office Requirement: 4 days a week
Responsibilities
AI & Software Engineering
Reliability & Operations
Stakeholder Management & Influence
Team Contribution & Leadership
- Translate ambiguous stakeholder needs into clear, testable AI system requirements.
- Design, build, and maintain AI workflows as clean, maintainable, testable, and observable systems that are safe to change.
- Own the data contracts, context boundaries, and system inputs your workflows depend on.
- Define what can run autonomously, what requires human review, and when escalation is required.
- Build identity, permissions, audit trails, and trust boundaries into system design.
- Make pragmatic trade-offs across cost, latency, reliability, autonomy, and user experience within clear security and compliance guardrails.
Reliability & Operations
- Build eval harnesses, regression suites, and release checks for non-deterministic behavior.
- Develop CI/CD and testing practices that let the team ship AI changes safely and quickly.
- Implement logging, tracing, and observability based on mapped failure modes, so issues are visible, explainable, and recoverable. Build error handling, fallback paths, and operational resilience across AI pipelines.
Stakeholder Management & Influence
- Partner with DevOps, data engineering, security, and technology solutions teams to productionize AI systems.
- Help stakeholders distinguish between automation, decision support, and human-accountable work.
- Manage competing priorities across stakeholders with clarity and discipline.
- Present technical findings, trade-offs, and risks clearly to executive, technical, and business audiences.
- Help foster a data-driven, AI-literate culture across the firm.
Team Contribution & Leadership
- Operate with a manager mindset: set standards, mentor contract engineers, and improve ways of working.
- Contribute to AI engineering standards for evals, versioning, releases, and ownership.
- Design reusable platform patterns so new AI use cases do not rebuild the same foundations.
- Apply AI-assisted development tools effectively and raise the team’s standard of use.
Qualifications
Education & Certificates
- Bachelor’s degree, required
- Concentration in Computer Science, Engineering, Information Systems, Data Science, or a related technical field, preferred
Professional Experience
- Minimum 5+ years of overall relevant experience, required
- Hands-on software, platform, infrastructure, or data engineering experience building production systems, preferred
- Experience with full-stack, backend, infrastructure, or data-intensive systems.
- Experience designing and shipping AI-enabled applications, workflow automation, agentic systems, or model-integrated products (preferred).
- Experience owning production systems, including testing, observability, deployment, and operational support.
Competencies & Attributes
- Experience with modern languages and frameworks. Python and TypeScript are our primary languages, with React experience useful. We are polyglot-friendly: if you learn quickly and build deeply, the exact stack matters less.
- Strong systems thinker who can turn ambiguous stakeholder needs into clear, testable technical requirements.
- Production-minded engineer who values reliability, maintainability, observability, and safe change management.
- Comfortable building with non-deterministic systems. LLM outputs vary by nature, so you know how to design, monitor, test, and iterate without relying only on deterministic testing.
- Strong understanding of data contracts, context management, permissions, auditability, and system trust boundaries.
- Clear communicator who can explain technical trade-offs, risks, and recommendations to executive, technical, and business audiences.
- Genuine passion for AI and emerging technologies, paired with practical judgment about where they create real business and operational value.
Benefits/Compensation
The compensation range for this role is specific to Washington, DC and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.
The anticipated base salary range for this role is $150,000 to $170,000.
In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.
Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by Carlyle.
Company Information
The Carlyle Group (NASDAQ: CG) is a global investment firm with $475 billion of assets under management, across 678 investment vehicles as of March 31, 2026. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,500 professionals operating in 28 offices in North America, Europe, the Middle East, Asia and Australia.
Carlyle’s purpose is to connect people, ideas, and capital to fuel growth for companies and performance for investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments – Global Private Equity, Global Credit and Carlyle AlpInvest – and has deep expertise across industries, markets, and geographies.
At Carlyle, we believe that a wide spectrum of experiences and viewpoints drives performance and success. Our CEO, Harvey Schwartz, has stated that, "To build better businesses and create value for all of our stakeholders, we are focused on assembling leadership teams with the strongest insights from a range of perspectives." Reflecting this view, emphasis is placed on development, retention and inclusion through our internal processes and seven Employee Resource Groups (ERGs). We cultivate a culture where ideas are openly shared and challenged, connecting diverse expertise and perspectives to drive enduring value.