Forward Deployed Product Engineer

Requirements

• Education & Certificates
• Bachelor’s degree, required.
• Concentration in computer science, engineering, or a related quantitative field, preferred.
• Master’s degree, preferred.
• Professional Experience
• Minimum of 10 years of relevant software engineering experience, required, with a track record of increasing technical scope and ownership.
• Demonstrated history of owning business-critical applications end-to-end and delivering measurable business outcomes, required.
• Hands-on experience building production systems using Python, with strong experience across enterprise data platforms and databases (e.g., Snowflake, Databricks, PostgreSQL, MS SQL).
• Frontend development experience with React and/or Next.js.
• Experience developing or integrating production AI-enabled applications, including LLMs, RAG pipelines, and orchestration frameworks (e.g., LangChain, LlamaIndex); familiarity with enterprise LLM platforms such as AWS Bedrock or Anthropic Claude, preferred.
• Experience partnering directly with business or investment users in an embedded / forward-deployed delivery model, strongly preferred.
• Experience providing technical leadership to engineering teams, including coordinating onshore and offshore delivery, preferred.
• Prior experience in alternative asset management, private equity, or financial services, preferred.
• Competencies & Attributes
• Full-stack application development (Python; React / Next.js).
• API design and service-oriented architecture.
• Modern data platforms, relational databases, and data pipeline design.
• Applied AI and LLM integration (RAG, agentic workflows, prompt design).
• Strong product judgment and comfort working directly with business users in a fast-paced, delivery-focused environment.
• Technical leadership, mentorship, and the ability to set and enforce engineering standards across a team.
• Executive presence with excellent written and verbal communication.
• Ability to operate autonomously and drive outcomes in ambiguous problem spaces.
• 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 $210,000 to $220,000.
• 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.

Who We Are

Preferred Qualifications

• Concentration in computer science, engineering, or a related quantitative field, preferred.
• Master’s degree, preferred.
• Experience developing or integrating production AI-enabled applications, including LLMs, RAG pipelines, and orchestration frameworks (e.g., LangChain, LlamaIndex); familiarity with enterprise LLM platforms such as AWS Bedrock or Anthropic Claude, preferred.
• Experience partnering directly with business or investment users in an embedded / forward-deployed delivery model, strongly preferred.
• Experience providing technical leadership to engineering teams, including coordinating onshore and offshore delivery, preferred.
• Prior experience in alternative asset management, private equity, or financial services, preferred.
• 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.