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Contract Ai Prompt Engineer Jobs in Delaware (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 ... Define standards for advanced prompt engineering and context window management . * Own delivery of ...

Luxoft

AI & Platform Software Engineer

Wilmington, DE · On-site

$110 - $150/hr

... contract-to-hire in intent) carry the front-loaded build with capability transfer written in ... prompt engineering, RAG/context engineering, or agent-based automation). * Hands-on Azure ...

Photon

Lead AI Engineer | Onsite - Delaware

Wilmington, DE · On-site

$99K - $131K/yr

Define standards for advanced prompt engineering and context window management . * Own delivery of ... Drive delivery of AI agent and multi-agent systems and tool-use/MCP integration patterns. * Own ...

Luxoft

AI & Platform Software Engineer

Wilmington, DE · On-site

Hands-on experience with GenAI models and AI-assisted development workflows (coding assistants, prompt engineering, RAG/context engineering, or agent-based automation). * Hands-on Azure experience ...

Morson Talent

AI Adoption Specialist

Wilmington, DE · On-site +1

$35 - $45/hr

Contract Duration: 1 Year Rate: Up to $45/hour W2 + benefits Hours: 40 hours/week (8am - 4pm ... models and prompt engineering. Foundational ability to read and write Python for prototypes ...

Athena LLC

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Support the development of AI agentic components such as task planning, tool use, memory, prompt ...

Athenago

AI Engineering Intern

Wilmington, DE

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Support the development of AI agentic components such as task planning, tool use, memory, prompt ...

ClifyX

GenAI Engineer

Wilmington, DE · On-site

Python • AI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning • Frameworks: TensorFlow, PyTorch • GenAI Tools: LangChain, LlamaIndex • Vector DB: Pinecone ...

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Contract Ai Prompt Engineer information

What are the key skills and qualifications needed to thrive as a contract AI prompt engineer, and why are they important?

To thrive as a Contract AI Prompt Engineer, you need a solid understanding of natural language processing (NLP), machine learning concepts, and experience in designing effective prompts for AI models, often supported by a relevant degree or portfolio. Familiarity with AI platforms like OpenAI GPT, prompt engineering tools, and scripting languages such as Python is typically required. Strong problem-solving abilities, attention to detail, and clear communication skills help you collaborate with stakeholders and refine AI outputs. These skills are crucial to ensure the development of accurate, reliable, and user-friendly AI solutions for clients.

What is a contract AI prompt engineer?

Contract AI Prompt Engineers are professionals hired on a temporary or project basis to create, refine, and optimize prompts for artificial intelligence models, such as large language models (LLMs). Their main responsibility is to ensure AI systems understand and respond accurately to human input by designing effective queries and instructions. They work closely with clients or in-house teams to tailor prompts for specific business needs, improve model outputs, and sometimes help develop prompt libraries or documentation. As contractors, they typically work for a set duration or until a project is completed, providing specialized expertise without a long-term employment commitment.

What are some common challenges contract AI prompt engineers face when working with diverse clients?

As a Contract AI Prompt Engineer, you'll often work with clients from various industries, each with unique goals and expectations regarding AI-generated content. One common challenge is quickly adapting to different brand voices and technical requirements while ensuring prompts produce accurate and relevant outputs. Additionally, managing project timelines and communication remotely can require strong organizational skills. Collaborating effectively with cross-functional teams, such as data scientists and product managers, is also essential to deliver optimal prompt solutions.
What are the most commonly searched types of Ai Prompt Engineer jobs in Delaware? The most popular types of Ai Prompt Engineer jobs in Delaware are:
What are popular job titles related to Contract Ai Prompt Engineer jobs in Delaware? For Contract Ai Prompt Engineer jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Contract Ai Prompt Engineer jobs in Delaware look for? The top searched job categories for Contract Ai Prompt Engineer jobs in Delaware are:
What cities in Delaware are hiring for Contract Ai Prompt Engineer jobs? Cities in Delaware with the most Contract Ai Prompt Engineer job openings:
Contract Ai Prompt Engineer jobs near you
Infographic showing various Contract Ai Prompt Engineer job openings in Delaware as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Lead AI Engineer

Photon

Newark, DE • On-site

$100K - $132K/yr

Other

Posted 19 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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