Senior Developer, Applied AI

CFA Institute•Charlottesville, VA

2d•$106,000 - $170,000

About The Position

Are you a senior developer who thrives in collaborative environments and enjoys raising the bar for how teams build AI solutions? Do you bring both hands-on engineering depth and the ability to help shape standards, design patterns, and best practices within a growing AI Center of Excellence? Design, develop, and unit test end-to-end AI-enabled software solutions following standard software development lifecycle practices. Rapidly prototype AI capabilities from concept to demonstrable proof of value, including UI/API layers, orchestration, retrieval, and evaluation. Implement retrieval augmented generation (RAG) and enterprise search patterns, including connectors, chunking strategies, embeddings, access control, relevance tuning, and grounding/citation techniques. Build and orchestrate agentic workflows using tool/function calling, workflow orchestration, guardrails, observability, and error handling. Establish evaluation frameworks, including test datasets, golden answers, regression testing, hallucination detection, safety checks, and light red teaming. Package successful outcomes into reusable assets such as reference implementations, templates, prompt/tool patterns, and operational runbooks. Design technical solutions aligned with CFA Institute reference architectures and enterprise standards. Partner with subject matter experts and business stakeholders (e.g., Education, RAS, GCC) to define success criteria, ROI signals, and iterate on solutions. Transition production ready concepts to engineering and platform teams with clear requirements, architecture documentation, risks, and operational considerations. Contribute to and evolve coding standards, knowledge bases, and shared engineering practices. Translate business objectives into technical designs and support deployment, maintenance, and lifecycle management of applications.

Requirements

Bachelor’s degree in computer science or a related field, or equivalent practical experience.
Minimum of five (5) years of professional software development experience with a strong delivery track record.
Strong full stack and/or backend engineering experience, including API design and integration.
Hands‑on experience building generative AI solutions using platforms such as OpenAI, Azure OpenAI, or Anthropic, including prompt and tool orchestration and embeddings.
Proficiency in Python and/or TypeScript/Node.js.
Practical experience with search and retrieval technologies, including vector databases or enterprise search platforms.
Experience integrating enterprise systems and productivity platforms (e.g., Microsoft 365, Teams, SharePoint, Atlassian, Salesforce).
Experience across all phases of the development lifecycle, including requirements, development, testing, deployment, and support.
Strong written and verbal communication skills, including the ability to deliver clear demonstrations of technical solutions.
Ability to work effectively in ambiguous environments with a bias toward rapid experimentation and learning.

Nice To Haves

Experience in education technology, assessment systems, simulations, scoring, or human in the loop review workflows.
Familiarity with Microsoft Copilot Studio, M365 Copilot extensibility, Graph connectors, and Teams/SharePoint integration.
Experience with observability and evaluation tooling, including tracing, prompt/version management, and experiment tracking.
Familiarity with responsible AI practices, including data handling, privacy/PII considerations, access controls, auditability, and compliance.
Experience with CI/CD pipelines, automated testing, performance monitoring, and cloud-native deployment patterns.

Responsibilities

Design, develop, and unit test end-to-end AI-enabled software solutions following standard software development lifecycle practices.
Rapidly prototype AI capabilities from concept to demonstrable proof of value, including UI/API layers, orchestration, retrieval, and evaluation.
Implement retrieval augmented generation (RAG) and enterprise search patterns, including connectors, chunking strategies, embeddings, access control, relevance tuning, and grounding/citation techniques.
Build and orchestrate agentic workflows using tool/function calling, workflow orchestration, guardrails, observability, and error handling.
Establish evaluation frameworks, including test datasets, golden answers, regression testing, hallucination detection, safety checks, and light red teaming.
Package successful outcomes into reusable assets such as reference implementations, templates, prompt/tool patterns, and operational runbooks.
Design technical solutions aligned with CFA Institute reference architectures and enterprise standards.
Partner with subject matter experts and business stakeholders (e.g., Education, RAS, GCC) to define success criteria, ROI signals, and iterate on solutions.
Transition production ready concepts to engineering and platform teams with clear requirements, architecture documentation, risks, and operational considerations.
Contribute to and evolve coding standards, knowledge bases, and shared engineering practices.
Translate business objectives into technical designs and support deployment, maintenance, and lifecycle management of applications.