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Llm Ai Jobs (NOW HIRING)

Photon

Lead AI Engineer

Newark, DE · On-site

$100K - $132K/yr

... Lead AI Engineer Newark, DE - Onsite Responsibilities Owns end-to-end delivery of how the ... Own delivery of LLM API integration and SDK patterns used across applications. * Set organizational ...

Tenex.AI Inc

Principal Product Manager - AI

Deep LLM & AI Knowledge: Strong understanding of how LLMs, multi-agent architectures, and RAG pipelines can be leveraged to automate security analyst workflows. * Cybersecurity Expertise: Deep domain ...

Aperia

AI Engineer (LLMs + C#)

Alpharetta, GA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking an experienced AI/LLM Software Engineer to join our growing development team and help design, build, and integrate intelligent solutions into modern enterprise applications. The ideal ...

Northern Base

AI/LLM Engineer

New York, NY · On-site

Hiring Alert | AI/LLM Engineer Location: Edison, NY (Hybrid - 3 Days Onsite) Employment Type: Full-Time Experience Required: 8-10 Years Visa Type: USC / GC Only Interview Mode: In-person (Final Round ...

New

Aperia

AI Engineer (LLMs + C#)

Alpharetta, GA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking an experienced AI/LLM Software Engineer to join our growing development team and help design, build, and integrate intelligent solutions into modern enterprise applications. The ideal ...

New

Horizon3.ai

Staff Attack Engineer, AI/LLM

  • Medical

  • Dental

  • Vision

  • PTO

Essential Functions Attacking AI/LLM Systems * Break AI and agentic systems and translate that research into automated, repeatable attack modules for NodeZero. * Design and execute prompt injection ...

Autonomize AI

ML/LLM Engineer - Applied AI

Austin, TX · On-site

Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. They are seeking a hands-on ML/LLM Engineer to build and optimize AI-native systems that blend structured and ...

FurtherAI Inc

Senior AI Engineer - Agent Team

San Francisco, CA · On-site

$120 - $150/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Stay on top of emerging research and blogs on LLM/AI agents and bring ideas into production experiments. What We're Looking For * Amazing ability to speak with LLMs - Occam's razor in prompting

acralending

AI Engineer

Irvine, CA

LLM & AI Engineering * Implement Retrieval-Augmented Generation (RAG) systems using lending guidelines, overlays, investor matrices, and SOPs. * Build prompt orchestration, memory systems, and agent ...

acralending

AI Engineer

Irvine, CA

LLM & AI Engineering * Implement Retrieval-Augmented Generation (RAG) systems using lending guidelines, overlays, investor matrices, and SOPs. * Build prompt orchestration, memory systems, and agent ...

Digital Links Inc

Java AI/LLM

Glen Lyn, VA · Remote

$52.25 - $67.50/hr

AI/LLM skill with * AI/LLM - hugging face model, OLAMA, LLAMA, Mistral * Agentic AI, Open AI, Gemini * Fine tuning of LLM * Lang chain, Lang flow, FAISS, vector database, Cosine similarity search.

Beacon Systems, Inc

Senior Data Architect

Bernardsville, NJ · On-site

$69.50 - $93/hr

Key Responsibilities: 1. LLM & AI Agent Architecture * Design and implement LLM-enabled architectures, including RAG * (Retrieval-Augmented Generation) solutions using structured and unstructured ...

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Llm Ai information

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$41K

$63.3K

$95.5K

How much do llm ai jobs pay per year?

As of Aug 14, 2026, the average yearly pay for llm ai in the United States is $63,311.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,000.00 and $69,500.00 per year, depending on experience, location, and employer.

What does an LLM AI do?

A typical day for someone in an LLM AI position involves designing, training, and evaluating large language models, collaborating with data scientists and software engineers, and reviewing system outputs for quality and accuracy. Professionals often attend team meetings to discuss project milestones, research new advancements, and troubleshoot model performance issues. The role tends to be highly collaborative, requiring frequent knowledge-sharing and coordination with other AI specialists, product managers, and, in some cases, external stakeholders. Staying up-to-date with the latest advancements in natural language processing and AI is an essential part of the job, ensuring that models remain state-of-the-art and impactful.

What are the key skills and qualifications needed to thrive in the LLM AI position?

To excel in an LLM AI (Large Language Model AI) role, candidates generally need a strong background in computer science, machine learning, and natural language processing, often supported by advanced degrees and experience with AI research or engineering. Familiarity with tools like Python, TensorFlow, PyTorch, and cloud computing platforms, as well as certifications in AI or data science, is highly valued. Excellent problem-solving, collaboration, and communication skills set standout professionals apart, enabling them to work effectively on cross-disciplinary teams. These skills and qualifications are crucial for developing, fine-tuning, and deploying cutting-edge language models that drive real-world AI applications.

What jobs can you do with an Llm Ai?

An LLM AI can be used in roles such as AI research scientist, machine learning engineer, data scientist, natural language processing specialist, or AI product developer. These jobs typically require skills in programming, data analysis, and understanding of AI models, often involving tools like Python and TensorFlow. Such positions are found in technology companies, research institutions, and startups focused on AI development.

What is an LLM AI?

An LLM AI job involves working with large language models (LLMs) to develop, train, optimize, and integrate AI-powered applications. Responsibilities may include natural language processing (NLP), prompt engineering, fine-tuning models, and ensuring ethical AI usage. These roles are common in AI research, software development, and data science fields.

Which Llm Ai is most in demand?

The most in-demand LLM AI roles typically involve expertise in natural language processing, machine learning, and deep learning frameworks such as TensorFlow or PyTorch. Skills in model fine-tuning, data management, and familiarity with popular models like GPT, BERT, or RoBERTa are highly sought after by employers across industries including tech, healthcare, and finance.
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Llm Ai jobs near you
Infographic showing various Llm Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $63,311 per year, or $30.4 per hour.

Lead AI Engineer

Photon

Newark, DE • On-site

$100K - $132K/yr

Other

Posted 24 days ago

Job description

Hi,

Hope you are doing well,

Myself Mankar from Photon and I have a position with our direct client, please send me your updated resume if you are interested and you can connect me through

Lead AI Engineer

Newark, DE - Onsite

Responsibilities

Owns end-to-end delivery of how the organization builds LLM-powered applications: SDK/integration architecture, retrieval and agent design, guardrails, and evaluation. Makes the calls on which LLMs to use for which use cases and sets the observability/cost discipline around AI systems, but is measured on shipped outcomes runs the offshore team day-to-day and stays hands-on to unblock delivery risk.

Description for Internal Candidates

Key Responsibilities

  • Own delivery of LLM API integration and SDK patterns used across applications.
  • Set organizational guidance on which LLM to use for what use case and drive delivery of multi-LLM scenarios.
  • Define standards for advanced prompt engineering and context window management.
  • Own delivery of RAG systems, including vector database selection/topology and knowledgebase design.
  • Drive delivery of AI agent and multi-agent systems and tool-use/MCP integration patterns.
  • Own guardrails delivery (safety, compliance, PII handling in prompts/outputs) critical in a financial-services context.
  • Define evaluation frameworks and real-time eval strategy; set standards for AI testing in CI/CD.
  • Own latency profiling, AI observability, and cost tracking/management for LLM-backed systems.
  • Run day-to-day delivery of the offshore development team: sprint commitments, code/design review, real-time unblocking, and hands-on work on critical-path AI features.
  • Report delivery status, risks, and blockers to engineering leadership.

Must-Have Qualifications

  • 6+ years in software engineering, with 2+ years as a tech lead owning end-to-end delivery of LLM/AI-powered systems (not a pure design/review architect role).
  • Proven track record of shipping AI-powered features on committed timelines, including hands-on troubleshooting under delivery pressure.
  • Strong, hands-on Python skills at an architectural/systems level.
  • Proven experience architecting LLM API integrations and SDK-level abstractions across multiple providers.
  • Demonstrated judgment on model selection (cost, latency, capability trade-offs) across use cases.
  • Deep expertise in prompt engineering and context window management at scale.
  • Proven design experience with RAG systems, including vector database architecture and knowledgebase design.
  • Experience architecting AI agents/multi-agent systems and tool-use patterns (MCP or equivalent).
  • Strong understanding of guardrails design content safety, PII protection, compliance controls for AI outputs.
  • Experience defining evaluation frameworks and integrating AI testing into CI/CD.
  • Proven ability to design for latency, observability, and cost management of AI systems in production.
  • Financial-services or regulated-industry experience strongly preferred given compliance/guardrail stakes.
  • Strong stakeholder communication; able to directly manage day-to-day delivery of an offshore team (standups, unblocking, sprint accountability).

Nice-to-Have Qualifications

  • Direct experience with specific frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent).
  • Experience with AWS Bedrock or comparable managed LLM platforms.
  • Contributions to or deep familiarity with MCP (Model Context Protocol) implementations.
  • Experience building internal LLM gateways.
  • Familiarity with responsible-AI/model-risk-management frameworks used in financial services.

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