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Context Engineering Jobs (NOW HIRING)

Context Engineer

Minneapolis, MN · On-site

$80K - $140K/yr

As a Context Engineer (Prompt Analyst), you will focus on: • Creating high-quality saved prompts ... Work with the Agent Lead and AI Engineering to: * Build and test prompts used inside agent ...

Context Engineer

Minneapolis, MN · On-site

$80K - $140K/yr

As a Context Engineer (Prompt Analyst), you will focus on: Creating high-quality saved prompts that ... Work with the Agent Lead and AI Engineering to: * Build and test prompts used inside agent ...

This role supports model lifecycle and risk governance through domain aware context engineering. Key Responsibilities * Design and optimize prompting and contextual structures to shape model behavior.

Sr Staff AI Engineer, Context Engineering

Chicago, IL

$107.70K - $147.90K/yr

While your core expertise lies in distributed systems, cloud-native architecture, and platform engineering, you will apply these skills specifically to the "Context Layer"-the specialized ...

OR

$104.40K - $143.40K/yr

While your core expertise lies in distributed systems, cloud-native architecture, and platform engineering, you will apply these skills specifically to the "Context Layer"-the specialized ...

OR · On-site

$104.40K - $143.40K/yr

While your core expertise lies in distributed systems, cloud-native architecture, and platform engineering, you will apply these skills specifically to the "Context Layer"-the specialized ...

Sr Staff AI Engineer, Context Engineering

$107K - $146.90K/yr

While your core expertise lies in distributed systems, cloud-native architecture, and platform engineering, you will apply these skills specifically to the "Context Layer"-the specialized ...

... context engineering, contributing to standards adopted across the enterprise. • Contribute to code reviews, technical discussions, and the growth of the broader team. Qualifications : Required ...

... context retrieval. * Agentic R&D & Prototyping: Hands-on prototyping of emerging architectural patterns, such as Multi-Agent Orchestration and autonomous long-term memory management. * Engineering ...

OR

$140.20K - $185.80K/yr

... context retrieval. * Agentic R&D & Prototyping: Hands-on prototyping of emerging architectural patterns, such as Multi-Agent Orchestration and autonomous long-term memory management. * Engineering ...

OR

$140.20K - $185.80K/yr

... context retrieval. * Agentic R&D & Prototyping: Hands-on prototyping of emerging architectural patterns, such as Multi-Agent Orchestration and autonomous long-term memory management. * Engineering ...

... context engineering, contributing to standards adopted across the enterprise. - Contribute to code reviews, technical discussions, and the growth of the broader team. What You Need to Succeed ...

... context engineering, contributing to standards adopted across the enterprise. - Contribute to code reviews, technical discussions, and the growth of the broader team. What You Need to Succeed ...

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Context Engineering information

See salary details

$46.5K

$146.9K

$174K

How much do context engineering jobs pay per year?

As of Jun 1, 2026, the average yearly pay for context engineering in the United States is $146,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $173,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Context Engineering jobs? Cities with the most Context Engineering job openings:
Infographic showing various Context Engineering job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $146,868 per year, or $70.6 per hour.

LLM/Prompt-Context Engineer - Fullstack Python (AI Agents, LangGraph, Context Engineering)

Diversity Nexus

Atlanta, GA • On-site

Other

Posted 22 days ago


Job description

5 openings
Tech M TechM182458
TechM182470
TechM182471
TechM182472
TechM182483 LLM/Prompt-Context Engineer - Fullstack Python
(AI Agents, LangGraph, Context Engineering)
Location -
1st Atlanta,
2nd Dallas,
3rd Seattle Onsite Pay rate:TBD
Telecommunication LLM/Prompt-Context Engineer - Fullstack Python (AI Agents, LangGraph, Context Engineering)
Location - 1st Atlanta, 2nd Dallas, 3rd Seattle (Onsite no remote).
Onsite interview required

We are looking for a highly skilled LLM/Prompt-Context Engineer with a strong fullstack Python background to design, develop, and integrate intelligent systems focused on
large language models (LLMs), prompt engineering, and advanced context management. In this role, you will play a critical part in architecting context-rich AI solutions,
crafting effective prompts, and ensuring seamless agent interactions using frameworks like LangGraph.
Key Responsibilities:
Prompt & Context Engineering:
Design, optimize, and evaluate prompts for LLMs to achieve precise, reliable, and contextually relevant outputs across a variety of use cases.
Context Management:
rchitect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization, to enhance agent performance.
LLM Integration:
Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment.
LangGraph & Agent Flows:
Build and manage complex conversational and agent workflows using the LangGraph framework to support multi-agent or multi-step solutions.
Full Stack Development:
Develop robust backend services, APIs, and (optionally) front-end interfaces to enable end-to-end AI-powered applications.
Collaboration:
Work closely with product, data science, and engineering teams to define requirements, run prompt experiments, and iterate quickly on solutions.
Evaluation & Optimization:
Implement testing, monitoring, and evaluation pipelines to continuously improve prompt effectiveness and context handling.
Required Skills & Qualifications:
Deep experience with full stack Python development (FastAPI, Flask, Django; SQL/NoSQL databases).
Demonstrated expertise in prompt engineering for LLMs (e.g., OpenAI, Anthropic, open-source LLMs).
Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies.
Hands-on experience integrating AI agents and LLMs into production systems.
Proficient with conversational flow frameworks such as LangGraph.
Familiarity with cloud infrastructure, containerization (Docker), and CI/CD practices.
Exceptional analytical, problem-solving, and communication skills.
Preferred:
Experience evaluating and fine-tuning LLMs or working with RAG architectures.
Background in information retrieval, search, or knowledge management systems.
Contributions to open-source LLM, agent, or prompt engineering projects.