AI Engineer

Charity Navigator is the worlds largest and most-utilized independent nonprofit evaluator. The organization guides informed giving by evaluating the financial health accountability transparency and impact of charities and provides data on over 245000 nonprofits. As a 501(c)(3) public charity itself Charity Navigator depends on support from individuals corporations and foundations to provide this trusted data free of charge to the public.

You will build and ship production LLM-powered and agentic features that make 2.4 million nonprofit profiles easier to search compare and understand - so a donor gets a clear answer instead of a spreadsheet.

This is application-layer work. You will partner with our existing engineering team rather than owning the pipelines yourself so your time goes into the AI features people use.

You will report to the VP of Engineering and work closely with them and other senior engineers on system design technical direction and strategic AI opportunities. You will own AI features from day one with regular design review and hands-on guidance on the harder architectural calls and take on more architectural ownership as you build depth in production AI systems.

• Build and ship production LLM-powered and agentic features - prompt orchestration tool calling embeddings structured outputs - favoring reusable components over one-off solutions.
• Build API Integrations MCP servers and retrieval-augmented generation (RAG) workflows that connect our existing data systems to vector search so that AI features surface and explain our published ratings data accurately and cite the source of each figure.
• Build and run evaluation infrastructure - prompt regression tests LLM-as-a-judge evaluations synthetic datasets - that catch feature quality regressions before users do.
• Monitor AI features in production. Track accuracy latency token cost and hallucination rates then debug and tune prompts based on what you find.
• Implement runtime safety and reliability guardrails that keep AI outputs within quality compliance and operational bounds.
• Research and recommend orchestration frameworks vector stores and model providers weighing cost and operational burden against speed. Final build-versus-buy calls are made jointly with the VP of Engineering.
• Work directly with non-technical stakeholders to scope problems and give them honest assessments of what AI can and cannot do.
• Evaluate emerging models and tools use AI-assisted development extensively and help raise team engineering standards through code review.
• What We Look For

• 2-3 years building or deploying machine learning models or AI-driven applications.
• Education
• Bachelors degree in Computer Science Engineering AI/ML or a related field or a relevant certificate program. Demonstrated technical proficiency and relevant industry experience will be considered in lieu of a formal degree.
• Required
• Python and ML fundamentals. 2 years of Python professional or substantial project-based experience with a solid grasp of core machine learning concepts and API integration.
• LLM and agentic systems. Hands-on experience with foundation model providers (Anthropic OpenAI and similar) prompt engineering and agentic patterns - using orchestration frameworks such as LangChain or LlamaIndex or integration standards such as the Model Context Protocol.
• Retrieval and data integration. Practical experience querying and tuning a vector database (pgvector OpenSearch or similar) for RAG applications.

• Managed cloud AI services such as Amazon Bedrock are preferred.
• Cloud deployment of application code via serverless or containerized patterns AWS required.
• Scrum or other Agile development experience.
• Cloud Gen AI or machine learning certifications such as AWS Certified Generative AI Developer Certified Machine Learning or Solutions Architect.

• Resourcefulness and adaptability. You learn quickly against unfamiliar problems new ideas and changing technology and you find a way through when the obvious path is blocked.
• Accountability and trust. Direct truthful communication. You keep your commitments admit mistakes and correct them and give peers respectful open-minded feedback.
• Comfort with ambiguity. When requirements are incomplete or still moving you surface the open questions early and bring options rather than assumptions.
• Translation. You can explain what AI can and cannot do to people who do not build it and turn their problems into a technical scope in both directions.
• Coachability. You seek feedback and apply it quickly. You treat design and code review as a learning loop rather than a checkpoint to clear and you are comfortable saying I dont know yet and going to find out.

Location & Work Environment

This position is fully remote within the United States requiring a quiet professional home setup for video collaboration. Computer provided. Occasional travel to team retreats or key strategic meetings may be required.

Compensation & Benefits

Salary Range: Our expected hiring range for this role is $105000 $125000 with actual placement depending on experience skill alignment and qualifications. Because this is a new role for our team we remain flexible for exceptional candidates whose background exceeds our core requirements.

Standard Benefits Package:

• Health Dental and Vision Insurance (including coverage for dependents)
• Life & Disability Insurance
• 20 vacation days 10 sick days 11 paid holidays in your first year
• Retirement savings with up to 3% match of base salary
• Flexible spending and dependent care accounts

Equal Opportunity Employer: Charity Navigator provides equal employment opportunities to all employees and applicants for employment regardless of their race color creed religion sex gender disability genetics or any other characteristics protected by federal state or local law.

Work Authorization: Only candidates who are legally authorized to work in the United States (and currently residing in the US) should apply.