Advisory Research Software Engineer
Indexed description
- Design and implement AI systems that address complex SQL and data transformation tasks requiring multi-step reasoning beyond single-pass generation approaches.
- Lead the technical development of the Query Planning Gym (QueryGym) framework to support structured reasoning and evaluation on enterprise-scale workloads.
- Architect agent-based workflows within QueryGym to support planning, validation, critique, and repair as coordinated system components.
- Integrate execution-aware tools into agent workflows to improve correctness, reduce retries, and optimize system efficiency.
- Translate research concepts in reasoning and planning into product-compatible architectures, develop production-grade code, testing systems, benchmarking performance, and analyzing results.
- Integrate and analyze benchmarks such as ELTBench against QueryGym for evaluating complex, real world SQL transformation workloads.
- Develop algorithms and agentic systems that improve LLM reliability.
- Collaborate with product teams to analyze production data transformation pipelines and identify schema drift and execution issues.
- Develop remediation approaches that translate plan level failures into actionable configuration or transformation guidance for users, including validation using benchmarks.
- Work on design and implementation of autonomous agents for AppWorld.
- Prepare technical documentation, design specifications, and implementation guidance for downstream teams to operationalize developed systems.
- Prepare research publications and end-to-end demonstrations to communicate system capabilities to internal and external audiences.
- Design and implement a synthetic dataset and benchmark generation pipeline for long, complex SQL queries.
- Utilize: Python, Transformer Architecture, Data & AI LLMs (Fine Tuning, Inference, Evaluation), Container Orchestration Platforms (Kubernetes, Docker, OpenShift), Data & AI Microservice deployment, Agentic AI frameworks, Natural Language Processing (NLP).
Required Technical And Professional Expertise
Master’s degree or equivalent in Computer Science or related (employer will accept a Bachelor's degree plus five (5) years of progressive experience in lieu of a Master’s degree) and one (1) year of experience as a Research Software Engineer or related. One (1) year of experience must include utilizing Python, Transformer Architecture, Data & AI LLMs (Fine Tuning, Inference, Evaluation), Container Orchestration Platforms (Kubernetes, Docker, OpenShift), Data & AI Microservice deployment, Agentic AI frameworks, Natural Language Processing (NLP).
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