Tech Lead, Software Engineer - AI Agent Memory Infrastructure

ByteDance; San Jose (CA); On-site; USD 244,800 - 588,000; Full time

Benefits offered by this job

Medical/Dental/Vision insurance

401(k) matching

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Holidays

Sick days

Personal time

Job summary

ByteDance is hiring for Tech Lead, Software Engineer - AI Agent Memory Infrastructure in San Jose. You will help design and operate memory infrastructure for long-term and conversational AI, enabling personalized and context-aware experiences.

You will collaborate with model, product, and platform teams to productionize memory capabilities, optimize performance, latency, and cost, while exploring novel memory representations and multimodal data support.

Qualifications

• Bachelor’s degree or higher in CS/AI/DS or related fields.
• Strong experience in distributed systems, databases, or AI infrastructure.
• Proficient in Go, Python, or C++ with coding best practices.

Responsibilities

• Design and evolve memory infrastructure for AI agents and long-term memory.
• Architect pipelines for low-latency, high-availability memory systems.
• Tackle memory representation, retrieval, ranking, and fusion challenges.
• Collaborate with model/product/platform teams to productionize memory capabilities.

Skills

Distributed systems

Databases

Information retrieval

Go

Python

C++

LLM embeddings

RAG

Context engineering

Memory systems

Education

Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Data Science, or related fields

Tools

mem0

memOS

memU

Job description

Tech Lead, Software Engineer - AI Agent Memory Infrastructure

Location: San Jose

Team: Technology

Employment Type: Regular

Job Code: A243679

Responsibilities

Join ByteDance’s AI Agent Memory Infrastructure team, where we build the core memory systems that power next-generation intelligent agents. Our focus is on creating a unified platform for long-term, conversational, and task-oriented memory, enabling more personalized and context-aware AI experiences.

We design and operate large-scale, low-latency, and highly reliable memory infrastructure, covering the full lifecycle from storage and retrieval to updating and optimization. Working at the intersection of LLMs, data systems, and context engineering, we tackle challenges in memory representation, retrieval, and multimodal fusion. Partnering closely with model and product teams, we turn advanced research into scalable production systems that support a wide range of AI-driven applications.

• Design, build, and evolve the next-generation memory infrastructure for AI agents, developing a unified platform that supports long-term memory, conversational memory, and task-oriented memory.
• Architect and optimize memory system pipelines for large-scale, low-latency, and high-availability environments, including data ingestion, storage, indexing, retrieval, updating, compression, and forgetting mechanisms to support real-time inference and personalized interactions.
• Explore key challenges at the intersection of large language models, context engineering, and data management, including memory representation, retrieval and ranking, conflict resolution, summarization and fusion, and memory lifecycle management.
• Design unified memory models and processing workflows for multimodal data (text, image, audio, behavioral signals), enhancing agents’ long-term consistency, personalization, and task completion in complex scenarios.
• Collaborate closely with model, application, and platform teams to productionize memory capabilities, and continuously optimize system performance across quality, latency, cost, reliability, and safety.
• Stay up-to-date with cutting-edge advancements and contribute to the long-term technical roadmap of AI agent memory systems, driving innovation and capability evolution.

Qualifications

Minimum Qualifications

• Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Strong experience in distributed systems, databases, information retrieval systems, or AI infrastructure, with proven system design and production engineering capabilities.
• Proficient in at least one programming language such as Go, Python, or C++, with strong coding standards and engineering best practices.
• Solid understanding of core technologies in LLM applications, including but not limited to embeddings, retrieval-augmented generation (RAG), context engineering, retrieval systems, and long-term state management.
• Familiarity with one or more key areas in memory systems: memory extraction and representation, vector/graph indexing, retrieval and ranking, memory updating, compression and forgetting, multimodal memory fusion.

Preferred Qualifications

• Experience in agent memory systems, user profiling, recommendation/search feature platforms, or knowledge base systems.
• Contributions to or deep understanding of open-source memory frameworks such as mem0, memOS, memU, or similar solutions.
• Strong track record in databases, information retrieval, machine learning, or AI systems, including publications, impactful open-source work, or notable technical achievements.
• Experience in multimodal data processing, online inference systems, personalized agents, or long-term user state modeling.
• Ability to analyze and optimize trade-offs across system performance, latency, cost, and scalability from both system and algorithm perspectives; experience with complex production systems is highly preferred.

Job Information

The base salary range for this position in the selected city is $244,800 – $588,000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits

• Day one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short-term and long-term disability coverage.
• Life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

For Los Angeles County (unincorporated) Candidates:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
3. Exercising sound judgment.

ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request.