Llm Engineer Jobs
Llm Engineer jobs are open across AI research labs, enterprise software, fintech, and healthtech, from junior to staff and principal levels, with specializations in retrieval-augmented generation, fine-tuning, and prompt engineering. Find a role that fits from the openings below and apply directly.
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Hi, Everyone
******W2 CONTRACT ONLY***W2 CONTRACT ONLY***W2 CONTRACT ONLY******
100% Closure \& Long-term project, Immediate Interview Surely
Job Title: AI/LLM Engineer
Location: San Jose CA
Contract: w2 Contract / c2c Contract
JD: We are looking for a highly skilled AI/LLM Engineer to design and build intelligent agent-based systems that can reason, plan, and act autonomously. The role requires strong Python engineering expertise and hands-on experience with modern agent frameworks, along with a solid understanding of data platforms and scalable architectures.
Key Responsibilities
- Agent \& AI System Development
- Design and build agent-based systems using frameworks such as LangChain, LangGraph, or similar
- Develop intelligent components capable of reasoning, planning, and executing tasks autonomously
-
Implement advanced cognitive patterns such as ReAct (Reasoning + Acting)
-
LLM Capabilities \& Enhancements
- Develop and integrate memory, tool usage, and context management capabilities (MCP)
- Build systems that leverage tool calling, chaining, and orchestration of LLM workflows
-
Collaborate with prompt engineers to enhance model responses and performance
-
Engineering \& Development
- Write high-quality, scalable code using Python (including async programming)
- Build and maintain APIs and microservices for AI/agent-based applications
-
Ensure systems are efficient, reliable, and production-ready
-
Guardrails \& Responsible AI
- Design and implement guardrails and safety mechanisms for LLM-driven systems
-
Ensure robust handling of edge cases, failure scenarios, and unintended outputs
-
Data \& Platform Integration
- Work with modern data platforms such as:
- Snowflake
- Databricks
- Lakehouse architectures
- Integrate AI solutions with enterprise data pipelines and systems
Skills:
- Digital : Artificial Intelligence(AI)
- Digital : Snowflake
- Digital : Databricks
- AI Agents
Experience Required: 8-10
NOTE: Please share your updated resume to c2c@galaxyitech.com
Hi, Everyone
******W2 CONTRACT ONLY***W2 CONTRACT ONLY***W2 CONTRACT ONLY******
100% Closure \& Long-term project, Immediate Interview Surely
Job Title: AI/LLM Engineer
Location: San Jose CA
Contract: w2 Contract / c2c Contract
JD: We are looking for a highly skilled AI/LLM Engineer to design and build intelligent agent-based systems that can reason, plan, and act autonomously. The role requires strong Python engineering expertise and hands-on experience with modern agent frameworks, along with a solid understanding of data platforms and scalable architectures.
Key Responsibilities
- Agent \& AI System Development
- Design and build agent-based systems using frameworks such as LangChain, LangGraph, or similar
- Develop intelligent components capable of reasoning, planning, and executing tasks autonomously
-
Implement advanced cognitive patterns such as ReAct (Reasoning + Acting)
-
LLM Capabilities \& Enhancements
- Develop and integrate memory, tool usage, and context management capabilities (MCP)
- Build systems that leverage tool calling, chaining, and orchestration of LLM workflows
-
Collaborate with prompt engineers to enhance model responses and performance
-
Engineering \& Development
- Write high-quality, scalable code using Python (including async programming)
- Build and maintain APIs and microservices for AI/agent-based applications
-
Ensure systems are efficient, reliable, and production-ready
-
Guardrails \& Responsible AI
- Design and implement guardrails and safety mechanisms for LLM-driven systems
-
Ensure robust handling of edge cases, failure scenarios, and unintended outputs
-
Data \& Platform Integration
- Work with modern data platforms such as:
- Snowflake
- Databricks
- Lakehouse architectures
- Integrate AI solutions with enterprise data pipelines and systems
Skills:
- Digital : Artificial Intelligence(AI)
- Digital : Snowflake
- Digital : Databricks
- AI Agents
Experience Required: 8-10
NOTE: Please share your updated resume to c2c@galaxyitech.com
See All 47+ Llm Engineer Jobs
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Find Llm Engineer JobsLlm Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- ByteDance9
- TikTok7
- Zoox5
- Microsoft3
- NVIDIA3
Top Industries Hiring
- Technology & Software22
- Media & Entertainment9
- Social Media8
- Electronics & Hardware6
- Artificial Intelligence5
What Employers Look For
The qualifications that appear most often in llm engineer jobs.
- Proficiency in Python and experience with PyTorch or JAX for model development and fine-tuning
- Hands-on experience with large language models such as GPT, LLaMA, Mistral, or Gemini families
- Familiarity with retrieval-augmented generation pipelines and vector databases like Pinecone or Weaviate
- Experience deploying and optimizing models for production inference using vLLM, TensorRT, or similar tools
- Strong understanding of prompt engineering, context window management, and evaluation frameworks
- Bachelor's or master's degree in computer science, machine learning, or a closely related technical field
Tips for Your Llm Engineer Job Search
Tailor your resume to model infrastructure
Recruiters scanning llm engineer resumes look for specifics: which foundation models you've worked with, whether you've handled inference optimization, and what serving frameworks you've used. Generic 'AI experience' won't stand out. Name the models, the frameworks, and the production scale.
Show evaluation results, not just experiments
Your portfolio should include benchmark results or qualitative eval outputs, not just notebooks. Teams want evidence you can assess model behavior systematically. Even a side project with a documented eval harness signals maturity that most candidates skip.
Filter openings by stack, not just title
LLM engineer job titles vary wildly. Search for 'applied scientist,' 'AI engineer,' and 'foundation model engineer' in addition to the exact title. Then filter by the stack listed in the description to find roles that match your strengths in tools like LangChain, vLLM, or Hugging Face.
Apply early to roles that fit
Migrate Mate lists llm engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for system-design questions on inference
Interviews for llm engineer roles frequently include a system-design round focused on latency, cost, and context management, not just model selection. Practice designing a retrieval-augmented pipeline end-to-end, including chunking strategy, vector store choice, and re-ranking logic.
Negotiate around compute access, not just salary
When you reach the offer stage, GPU access, cloud credits, and research time are negotiable at many AI teams. Ask specifically what compute budget the team works with and whether engineers have discretionary access. These resources affect what you can actually build.
Llm Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most llm engineers?
The companies hiring the most llm engineers right now include ByteDance, TikTok, and Zoox, with the largest share of openings in California, Washington, and North Carolina, based on current listings on Migrate Mate as of June 2026. Demand is concentrated at AI-native startups and large technology companies building internal generative AI products.
How many llm engineer jobs are remote?
About 9% of llm engineer openings are fully remote or hybrid as of June 2026, making it one of the more remote-accessible engineering disciplines. Roles focused on prompt engineering, evaluation, and RAG pipeline development tend to be the most remote-friendly, while positions involving on-premises GPU infrastructure or close cross-functional collaboration often require some on-site presence.
How do you become a llm engineer?
Start by building a strong foundation in Python and deep learning fundamentals, then work through the Hugging Face course and experiment with open-source models locally. Build at least one end-to-end project that includes fine-tuning or retrieval-augmented generation, document your evaluation process, and publish the code. Contributing to open-source LLM tooling and writing about your experiments publicly accelerates hiring significantly.
Can you get hired as a llm engineer without direct experience?
Yes, particularly at companies still building their AI teams from scratch. The most effective approach is demonstrating hands-on competence through a public portfolio: a fine-tuned model on Hugging Face, a documented RAG system on GitHub, or a technical write-up of an eval you designed. Hiring managers in this space weight demonstrated ability over credentials because the field is too new for long resumes to exist.
What does the llm engineer interview process look like?
Most processes include a recruiter screen, a technical phone interview covering Python and ML fundamentals, and a take-home or live coding round focused on a practical task like building a retrieval pipeline or evaluating model outputs. Final rounds typically include a system-design interview on inference architecture and a team-fit conversation. Some companies add a research presentation if the role involves novel modeling work.
Where can I find and apply to llm engineer jobs?
You can find and apply to llm engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your experience and stack, then apply directly to each one that fits. Openings are updated regularly, so checking back frequently gives you access to newly posted roles before they fill.
See All 47+ Llm Engineer Jobs
Jump back to the full list of openings and apply to any llm engineer role that fits.
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