Software Engineer, Applied Artificial Intelligence (AI)

ABS is seeking an exceptional Software Engineer to join our Applied Artificial IntelIigence (AI) Practice Team. In this full-time role, you will design, build, and deploy intelligent systems that move beyond research into production at scale. You will focus on architecting and evaluating multi-agent systems, retrieval-augmented generation (RAG) pipelines, and fine-tuned large language models delivering AI capabilities that drive measurable business impact.

What You Will Do:

• Build at the frontier: Design and implement end-to-end AI systems, including multi-agent workflows, retrieval pipelines, and customized LLMs.
• Engineer full-stack solutions: Deliver web and backend applications that seamlessly integrate AI, ensuring reliability, scalability, and strong user experience.
• Raise the bar on evaluation: Develop rigorous truth sets, automated quality checks, and real-time monitoring pipelines to quantify performance and business outcomes.
• Prototype rapidly: Transform research concepts into production-grade systems through fast iteration, disciplined testing, and continuous refinement.
• Shape best practices: Contribute to internal standards for applied AI development, evaluation, and deployment at scale.

What You Will Need:

Education and Experience

Bachelor’s degree in Computer Science, Engineering, or a related field. + years of software development experience, including + years building production-grade AI systems. Proven track record delivering AI agents, RAG pipelines, or fine-tuned models with measurable business impact. Experience designing evaluation frameworks and truth sets for applied AI quality assurance.

Knowledge, Skills, and Abilities

Strong expertise in agent frameworks and LLM orchestration (API-first development, Vercel AI SDK, LangChain, etc.). Deep knowledge of RAG architectures, embeddings, vector databases, and retrieval optimization strategies. Experience with LLM fine-tuning, prompt design, and model performance evaluation. Full-stack engineering skills across modern web and backend technologies. Familiarity with MLOps practices: CI/CD, model versioning, monitoring, and deployment at scale. Strong grounding in applied information retrieval and vector-based systems.

Reporting Relationships:

This role reports to a project manager and does not initially include direct reports.