Key Responsibilities

LLM Systems & Agents

·      Architect and build production LLM pipelines and multi-step agents, including tool use, retrieval, orchestration, and memory.

·      Treat reliability as a first-class concern: design for graceful degradation, retries, fallbacks, guardrails, and bounded failure modes.

·      Reduce hallucinations and unpredictable behavior through improved prompting strategies, structured outputs, validation, and grounding.

·      Optimize cost and latency across models, context strategies, caching, and routing.

Evaluation & Observability

·      Develop the evaluation and observability layer: offline evals, regression suites, tracing, and live monitoring of quality, cost, and latency.

·      Monitor system performance and proactively resolve complex production issues.

Platform & Application Development

·      Design and operate the scalable backend systems and data pipelines that support the LLM layer.

·      Ship production-ready features across front-end and back-end systems with strong attention to detail.

·      Work with cloud-based infrastructure and CI/CD pipelines to ensure smooth, safe, and frequent releases.

Technical Leadership & Collaboration

·      Establish engineering standards and patterns for LLM development across the broader team.

·      Maintain high standards for code quality through rigorous reviews, testing, and documentation; mentor junior and intermediate engineers.

·      Partner with product and engineering peers to assess feasibility and prototype rapidly.

·      Work directly with customers when necessary to help optimize complex enterprise workflows in our application.

Qualifications

·      Bachelor's degree in Computer Science, a similar technical field, or equivalent practical experience.

·      7+ years of professional software development experience, with a proven track record of building and maintaining complex, full-stack applications.

·      Hands-on experience building, benchmarking, and operating LLM-powered systems in production (pipelines, multi-step agents, advanced RAG, or similar).

·      Demonstrated experience owning architecture for distributed systems and raising engineering standards across a team.

Ranger AI Tech Stack

·      App: NextJS, NestJS, Python

·      Data: PostgreSQL, Vector Databases / Hybrid Search

·      Infrastructure: AWS (ECS, S3, RDS), Docker, CI/CD

·      AI: LLM APIs, embedding pipelines, agent orchestration, evaluation tooling