Manager, Autonomous Systems Engineering

Eightfold

🇺🇸In-Person - Bengaluru, IN1mo ago

Corporate Engineering AI Development Machine Learning Autonomous Systems Team Leadership Software Engineering

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Summary

Lead the design and deployment of AI agents and autonomous systems at Eightfold, architecting an agent stack that integrates Python, LLMs, and tool-calling for custom logic. Drive iterative quality improvements and metrics-driven leadership to transform QA through AI-enabled automation.

Key Responsibilities: Oversee the design, deployment, and refinement of AI agents for analyzing customer logs, identifying patterns, and autonomously suggesting test improvements. Define and track KPIs like Agent Accuracy Rate and RCA Lead Time Reduction while mentoring engineers and troubleshooting Python scripts and agent workflows hands-on.

Skills & Tools: Expertise in Python, AI agent architecture, LLM integration, RAG pipelines, and prompt engineering with a scientist's mindset for experimentation and troubleshooting. Strong strategic communication skills to translate QA strategies into technical requirements and foster a culture of building in public and sharing AI learnings.

Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or related quantitative field with 5+ years in Software Engineering or Quality Engineering. Minimum 2-3 years hands-on experience building and deploying AI-enabled applications and 2+ years in formal management or lead roles driving high-velocity engineering teams.

Location: Bengaluru, KA, IN

Job Description

Architect the Agent Stack: Lead the design and deployment of AI agents and Python for custom logic, tool-calling, and LLM integration. Drive Iterative Quality: Move beyond "it works" to "it's accurate." You will oversee the iterative refinement of agent prompts, RAG (Retrieval-Augmented Generation) pipelines, and output validation to ensure high-fidelity outcomes. Metrics-Driven Leadership: Define and track KPIs that actually matter: Agent Accuracy Rate, RCA Lead Time Reduction, and Test Coverage Expansion via AI. Bridge the Gap: Translate high-level QA strategies into technical requirements for AI agents that can analyze customer logs, identify patterns, and suggest test improvements autonomously. Hands-on Mentorship: Stay in the code. We need a leader who can troubleshoot a Python script or an agent workflow alongside their team when the going gets tough. Academic Foundation: Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or a related quantitative field. Proven Track Record : 5+ years in Software Engineering or Quality Engineering, with at least 2-3 years of hands-on experience building and deploying AI-enabled applications or automation frameworks. Leadership Experience: 2+ years in a formal management or lead role, specifically driving high-velocity engineering teams through the full development lifecycle. Soft Skills & Leadership Style The "Scientist" Mindset: A passion for experimentation. You don't get frustrated when an agent fails; you analyze the trace, adjust the prompt/data, and try again. Strategic Vision: The ability to explain to stakeholders how "AI for QA" translates to faster ship times and lower operational costs. Candor & Mentorship: A leader who provides direct, actionable feedback and fosters a culture of "building in public" and sharing AI learnings across the org.