Principal AI Engineer, Search AI
LinkedIn · Mountain View, CA, United States
- Senior
- Full-time
- $231,000 – $378,000
- Posted 2026-09-15
- Confirmed live on 25 September 2026
Job description
Job Description
Location:
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
This role will be based in Sunnyvale California, Bellevue Washington, or New York City.
Team Mission:
As we enter the biggest transformation of work in our lifetime, the majority of jobs on this planet will change over the next few years. Figuring out how humans find their path and earn a living is the most important problem in the world right now—and that’s what we’re solving on LinkedIn Search. Our mission is to connect every professional to the right people, knowledge, and opportunities.
What This Role Is:
As a Principal AI Engineer on LinkedIn Search, you will serve as the technical architect behind our shift from semantic search to Agentic Search. You will lead the technical vision and execution for multi-step reasoning, autonomous execution, tool/API orchestration, and conversational search workflows that understand complex intent, synthesize insights, and proactively take action on behalf of members.
Working across ranking, infrastructure, and multiple partner teams, you will architect the AI systems that turn static search results into an adaptive and agent-driven intelligence engine for 1B+ members.
What You’ll Do:
• Design Agentic Systems: Design and scale multi-agent reasoning frameworks, tool-use protocols, and memory systems, optimized for real-time search workflows.
• Drive Evals & Safety: Build rigorous evaluation harnesses and guardrails for non-deterministic agent workflows, ensuring enterprise-grade trust, attribution, and safety at global scale.
• Rapid AI Prototyping: Build runnable, state-of-the-art agentic POCs to prove out new paradigms (multimodal search, proactive task execution, autonomous candidate/job matching) and push them directly to production.
• Mentor & Elevate: Set technical standards, engineering best practices, and architectural principles for AI/LLM deployment across the broader search organization.
Why We Are Here:
Behind every search executed by our AI agents, there’s a human getting one step closer to paying their mortgage, funding a small business, or finding their dream career. Your responsibility is to build the underlying intelligence that turns those searches into real-world outcomes.
Core Responsibilities:
As a Principal AI Engineer and senior-level member of technical staff, you will deliver a combination of strategic thought leadership, innovation, and execution.
• Provide expert hands-on contribution
• Design multi-step reasoning frameworks, task planning systems, and tool-calling agents that solve complex operational or data challenges
• Define systems and standards for model evaluation, agent orchestration, and memory/context management
• Implement rigorous safety guardrails, error handling, logging, evaluation mechanisms, and fallback strategies for production LLMs.
• Serve as a Technical Leader, mentoring engineers and guiding complex technical decisions
Qualifications
Basic Qualifications:
• 7+ years of industry experience in software design, development, and algorithm related solutions.
• 5+ years in an Architect, Staff+, Principal, or equivalent technical leadership position
• Background in the following areas: Machine Learning and Artificial Intelligence
• BS (or higher, e.g., MS, or PhD) in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
Preferred Qualifications:
• 10+ years of overall experience including multiple years of high-level technical leadership, designing and implementing large-scale AI solutions related to ranking, retrieval, relevance, recommendations, personalization, and search.
• Active participation in open-source projects related to search, recommendation, or NLP and/or contributions to conferences such as NeurIPS, ICML, ACL, or RecSys.
• Hands-on understanding of agentic AI loops — how a model decides to call a tool / agent, how a result re-enters context, how loops terminate, and where they fail.
• Able to decompose a problem from a first-principles perspective.
• Able to communicate with equal ease with both engineers, product, and senior leadership.
Suggested Skills:
• Large Language Models (LLMs)
• Agentic AI
• AI Search & Recommendation Systems
You will Benefit from our Culture:
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 $231,000 to $378,000. Actual compensation packages are based on several factors that are unique to each
Interview problems reported for LinkedIn
Reported by candidates and public write-ups, not by LinkedIn. Practise each one here:
- Maximum Subarray — Medium
- Valid Parentheses — Easy
- Number of Islands — Medium
- Maximum Product Subarray — Medium
- Minimum Window Substring — Hard
- Search in Rotated Sorted Array — Medium
- Lowest Common Ancestor of a Binary Search Tree — Medium
- Maximum Depth of Binary Tree — Easy
- Serialize and Deserialize Binary Tree — Hard
- Merge Intervals — Medium
- Two Sum — Easy
- Merge Two Sorted Lists — Easy
- Merge K Sorted Lists — Hard
- Binary Tree Level Order Traversal — Medium
- Insert Interval — Medium
- Product of Array Except Self — Medium
- House Robber — Medium
- Palindromic Substrings — Medium
- Graph Valid Tree — Medium
- Number of Connected Components in an Undirected Graph — Medium
- Longest Substring Without Repeating Characters — Medium
- Same Tree — Easy
- Reorder List — Medium
- Invert Binary Tree — Easy
- Combination Sum — Medium
- Course Schedule — Medium
- House Robber II — Medium
- Word Break — Medium
- Unique Paths — Medium
- Best Time to Buy and Sell Stock — Easy
- Longest Consecutive Sequence — Medium
- Find Minimum in Rotated Sorted Array — Medium
- Reverse Linked List — Easy
- Linked List Cycle — Easy
- Validate Binary Search Tree — Medium
- Kth Smallest Element in a BST — Medium
- Longest Palindromic Substring — Medium
More at LinkedIn
- Learning Designer · San Francisco, CA, United States
- Senior Associate , Decision science · Bengaluru, KA, India
- Senior Account Executive, Marketing Solutions · Tokyo, 13, Japan
- Sales Strategy and Operations Associate · New York, NY, United States
- Staff Technical Program Manager · Mountain View, CA, United States
- Associate Engineer, Data Center · Manassas, VA, United States
- Sr. Program Manager, AI Initiatives, Go-To-Market Enablement · Sunnyvale, CA, United States
- Sr. Director, Software Engineering - Product Platform & Infrastructure · Mountain View, CA, United States