Key Responsibilities

• Build Agentic Systems – Implement multi-step reasoning agents with advanced memory, Retrieval-Augmented Generation (RAG), and integrations to tools, databases, and APIs.
• Evaluate and Optimize Agent Performance – Define and implement evaluation pipelines for agentic systems, including success/failure classification, grounding accuracy, reasoning robustness, tool-use reliability, and long-horizon task completion. Use metrics and benchmarks to continuously improve performance in production environments.
• Orchestrate & Optimize – Design supervisor/sub-agent patterns, enable coordination across agents, and apply best practices for robustness, performance, and scalability.
• Deploy & Evolve – Deliver production-grade agentic AI workflows on cloud platforms (AWS preferred), monitor and evaluate agent performance, and continuously fine-tune for quality and efficiency.
• Collaborate & Translate – Work with product managers, researchers, and engineers to transform complex chip design workflows into agent-driven, end-to-end solutions.

Desired Skillset Agentic AI Systems

• Hands-on experience with multi-agent orchestration and supervisor patterns.
• Familiarity with LangChain, LangGraph, LangSmith, or similar frameworks.
• Knowledge of RAG pipelines, memory management, and evaluation of agent performance.

Evaluation and Optimization

• Familiarity with agent evaluation frameworks (e.g., LangSmith evals, benchmark datasets, unit tests for agent workflows).
• Experience designing custom evaluation metrics for reasoning steps, tool use correctness, and RAG pipeline performance.
• Ability to balance automatic evaluation (synthetic benchmarks, self-play) with human-in-the-loop evaluation for complex workflows.

Cloud & Infrastructure

• Strong software engineering foundation with experience in cloud environments (AWS preferred).
• Knowledge of containerized deployment and backend integration.

Programming & Development

• Proficiency in Python; experience with backend systems and API integration.
• Familiarity with modern software engineering practices (GitHub, CI/CD pipelines, testing frameworks).

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering or a related field.
• 5-10 years of experience in software development in cloud environment
• 2+ years of experience with hands-on experience building and deploying production-grade agentic AI systems with real-world applications.
• Solid working knowledge of Retrieval-Augmented Generation (RAG), agent performance evaluation, and hands-on experience with LangGraph and LangSmith platforms.
• Proficiency in Python and familiarity with backend cloud services (preferably AWS).

Preferred Qualifications

• Contributions to open-source AI projects or frameworks.
• Experience with multi-agent orchestration patterns at scale.
• Knowledge of reinforcement learning, planning algorithms, or autonomous reasoning.
• Track record of deploying agentic AI systems in production at scale

What We Offer

• The chance to work on state-of-the-art AI systems that push the boundaries of autonomy and reasoning.
• A collaborative environment where engineering meets research.
• Competitive compensation and equity in a fast-growing AI startup.
• A culture that values ownership, curiosity, and technical excellence.

Featured Benefits

• Medical insurance
• Vision insurance
• Dental insurance
• 401(k)

Requirements Added By The Job Poster

• Working in an onsite setting
• Authorized to work in the United States