Manager, Software Engineering, CoreAI (HALO)

LinkedIn • Mountain View, CA

1d • $170,000 - $277,000 • Hybrid

About The Position

Team Overview: LinkedIn’s Core AI organization is dedicated to transforming the professional world through innovative solutions, including advanced models, agents, and AI systems. Our ‘HALO’ Evaluation Engineering team builds core technology that powers LinkedIn’s model and agent evaluation ecosystem. This is a horizontal and deeply cross-functional team empowering product, linguists, and operations partners to evaluate new AI solutions quickly, efficiently, and at scale. We’re building a next-generation AI evaluation and optimization platform that makes AI systems measurable, reliable, and continuously improving in production. As AI systems become more autonomous and agentic, evaluation can’t rely on manual labeling and disconnected tools. Our team is creating a unified intelligence layer that connects human feedback, AI judges, synthetic data, training pipelines, and real-time monitoring into a closed-loop improvement engine — defining how AI agents are validated, shipped, and improved at scale. Team Scope & Future Work Golden Dataset Generation Tools – Automate creation, labeling, quality control, and versioning of high-quality evaluation datasets from specs and production data. LLM-as-a-Judge Infrastructure – Build and align large model evaluators to reliably score outputs, reasoning traces, and agent behavior. Distilled In-House Evaluator Models – Convert large judges into efficient internal models for scalable, low-latency evaluation. Synthetic Data Generation – Generate controlled, edge-case, and stress-test datasets to expand coverage and robustness. Observability for AI Agents – Measure hallucinations, tool-use accuracy, reasoning quality, and convergence in real time. End-to-End Agent Evaluation Framework – Standardize offline benchmarking, regression testing, and production quality monitoring. Training Signal Pipeline (SFT & RLHF) – Turn evaluation signals and datasets into structured training data for continuous model improvement.

Requirements

• 5+ years of related industry experience in software/platform design, development, and related solutions
• 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
• BA/BS in Computer Science or other technical discipline, or related practical technical experience

Nice To Haves

• 2+ years of experience as a Technical Lead (Staff or Manager)
• 7+ years of overall experience including prior work with AI operations or related solutions.
• Experience building enterprise grade data platforms
• MS or PhD in Computer Science, Machine Learning, Statistics or related fields

Responsibilities

• Provide direct leadership for a team of 5-7 engineers.
• Work closely with various other teams across LinkedIn to align on initiatives, leveraging existing solutions, and ensure optimal collaboration.
• Participate in and facilitate technical and design discussions
• Contribute to the hands-on execution of technical solutions (coding, design, etc.).
• Leverage best practices & processes to ensure productivity of the team and drive faster iterations
• Attract world class talent and provide technical guidance, career development, and mentoring to team members.

Benefits

• We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
• LinkedIn is committed to fair and equitable compensation practices.
• The pay range for this role is $170,000 - $277,000.
• Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location.
• This may differ in other locations due to cost of labor considerations.
• The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans.
• For additional information, visit: https://careers.linkedin.com/benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager