Staff Engineer - ML/Agentic AI Developer

General Summary:

Staff Software Engineer Agentic AI in VLSI Domain Role Overview

We are looking for a Stafflevel Software Engineer to design and build AInative, agentic software systems used in complex, largescale engineering workflows. This role focuses on productiongrade software development, with strong ownership of automation, evaluation frameworks, benchmarking, grounded in a deep understanding of agentic architectures, system failure modes, and best practices for AInative software engineering.

Key Responsibilities

• Design, develop, and maintain AInative software platforms that orchestrate and evaluate agentbased workflows.
• Drive software architecture and design decisions to build scalable, modular systems with clear abstractions, robust interfaces, and sustainable engineering practices.
• Architect automation and evaluation frameworks to validate correctness, robustness, performance, cost, and stability of agentic systems.
• Build and own benchmarking pipelines that enable repeatable, comparable evaluation across models, agents, configurations, and releases.
• Apply strong engineering judgment around agentic system tradeoffs, including nondeterminism, feedback loops, toolinvocation failures, and error propagation.
• Establish best practices for productiongrade AI software, including modular design, observability, fault isolation, and reproducibility.
• Collaborate with software, ML, systems, and infrastructure teams to improve reliability and testability.
• Drive technical direction, engineering rigor, and code quality through design and code reviews.
• Mentor engineers and influence architecture through technical leadership.

Required Skills & Experience

• 8+ years of professional software engineering experience with ownership of complex, multicomponent systems.
• Strong proficiency in Python and experience building large, maintainable codebases and frameworks.
• Handson experience designing automation, evaluation, or testing frameworks for complex systems.
• Strong understanding of agentic system architectures, common failure modes, and operational pitfalls.
• Experience building CI/CD pipelines with automated quality, evaluation, and release gates.
• Solid grasp of distributed systems or platformscale software engineering concepts.
• Ability to reason about nondeterministic systems and design reliable evaluation strategies.
• Strong debugging skills and ability to collaborate across teams.

Preferred Qualifications

• Experience working with AI agents, orchestration frameworks, or multistep AI workflows.
• Exposure to benchmarking platforms, leaderboards, or evaluation harnesses.
• Familiarity with MLOps and observability platforms
• Familiarity with building scalable data pipelines
• Experience with HPC, heterogeneous compute, or largescale execution environments.
• MS or PhD in Computer Science, Electrical Engineering, or related field.

Minimum Qualifications:

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.