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Ai Prompt Engineer Entry Level Jobs in Washington

AI/ML Engineer Location: Remote Work Authorization: Must be able to work without sponsorship ... Advanced prompt-engineering experience for complex reasoning, extraction, orchestration, and ...

AI/ML Engineer Location: Remote Work Authorization: Must be able to work without sponsorship ... Advanced prompt-engineering experience for complex reasoning, extraction, orchestration, and ...

... prompt-level artifacts. • Build the agent layer by developing and refining the LLM-powered ... Company : BullFrog AI is a developer of an artificial intelligence platform intended to help ...

AI Engineer

Arlington, VA · On-site +1

$77K - $176K/yr

Share AI Engineer The Opportunity: As a programmer, you know that machine learning is critical to ... Experience with basic prompt engineering concepts and use of LLM SDKs or frameworks, including ...

Integrate AI capabilities into applications and workflows using modern orchestration frameworks ... You have strong prompt engineering and model alignment instincts for reliability and control. * You ...

Senior AI Solutions Engineer

Reston, VA

$57.50 - $74/hr

Familiar with generative AI concepts like RAG, prompt engineering, agents, structured output, multi-modal LLMs, and various embedding models * Strong programming skills in Python required. Experience ...

Gen AI/Python Developer

Reston, VA · On-site

$52.25 - $72/hr

Python * Gen AI * SQL * AWS Data Services * LLM * ML * Sagemaker * Bedrock Top 3 Soft Skills ... Experience working with LLMs (Anthropic Claude, Sonnet) and prompt engineering techniques. Strong ...

AI/Synthetic Engineer

Alexandria, VA · Hybrid

$110K - $135K/yr

This is an engineering role at heart but applied entirely to research questions. Responsibilities ... Build, tune, and maintain synthetic-audience models and the prompt/evaluation pipelines around them.

Applied AI Engineer

Arlington, VA · On-site

$159K - $263K/yr

Integrate AI capabilities into applications and workflows using modern orchestration frameworks ... You have strong prompt engineering and model alignment instincts for reliability and control. * You ...

AI QE Architect Location: Bethesda, MD (Hybrid) We are looking for strong AI Quality Engineering ... Hands-on experience with LLMs, prompt engineering, RAG, vector databases, and model evaluation

Engineer

Mclean, VA · On-site

$100K - $120K/yr

Conduct evaluations, A/B tests, and model drift checks while applying prompt engineering and optimization techniques. • Collaborate and Ensure Responsible AI : Partner with cross-functional teams ...

AI/Synthetic Engineer

Alexandria, VA · Hybrid

$110K - $135K/yr

This is an engineering role at heart but applied entirely to research questions. Work Environment ... Build, tune, and maintain synthetic-audience models and the prompt/evaluation pipelines around them.

Showing results 41-60

Ai Prompt Engineer Entry Level information

What is an AI prompt engineer at the entry level?

An entry-level AI Prompt Engineer is a professional who specializes in designing, testing, and refining prompts used to interact with AI language models like ChatGPT. Their main responsibility is to create effective prompts that guide AI systems to generate accurate, relevant, and useful responses for specific tasks or applications. Entry-level prompt engineers often work closely with data scientists, developers, and product teams to improve AI outputs, ensuring the technology meets user needs. This role requires strong analytical skills, creativity, and a basic understanding of natural language processing and machine learning concepts.

What is the difference between Ai Prompt Engineer Entry Level vs Ai Content Specialist?

AspectAi Prompt Engineer Entry LevelAi Content Specialist
Required CredentialsBasic knowledge of AI, programming, or linguistics; often a degree in related fieldsWriting, editing, or marketing background; often a degree in communications or related fields
Work EnvironmentTech companies, AI startups, or freelance projectsMedia agencies, content creation firms, or corporate marketing teams
Employer & Industry UsagePrimarily in AI development and machine learning industriesIn advertising, media, and digital marketing sectors

While both roles involve working with digital content and technology, Ai Prompt Engineers focus on designing prompts for AI models, whereas Ai Content Specialists create and manage content for various platforms. The roles share some technical skills but differ in their core responsibilities and industry applications.

Are AI prompt engineers in demand?

AI prompt engineers are increasingly in demand as organizations seek to optimize AI language models for various applications. The role requires skills in natural language processing, creativity, and familiarity with AI tools like GPT, with job growth driven by expanding AI adoption across industries.

What are the key skills and qualifications needed to thrive as an entry-level AI prompt engineer, and why are they important?

To thrive as an Entry-Level AI Prompt Engineer, you need a foundational understanding of natural language processing, prompt design, and basic programming skills, often supported by a degree in computer science or a related field. Familiarity with AI platforms like OpenAI, experience with prompt engineering tools, and basic knowledge of Python or similar languages are typically expected. Strong analytical thinking, creativity, and effective communication help you craft clear, high-performing prompts and collaborate with cross-functional teams. These skills are essential for developing accurate, user-friendly AI outputs and ensuring the practical success of AI-driven projects.

What are some common challenges faced by entry-level AI prompt engineers when working with large language models?

Entry-level AI Prompt Engineers often encounter challenges such as crafting effective prompts that elicit accurate and relevant responses from large language models. Balancing specificity and creativity while avoiding ambiguity can be tricky, and it's common to iterate multiple times before achieving the desired output. Additionally, understanding the model's limitations and biases is essential to avoid unintended results. Collaboration with data scientists and software engineers is frequent, as prompt engineers may need to integrate their work into larger AI systems or workflows.

How to get into AI prompt engineering?

To enter AI prompt engineering, develop strong skills in natural language processing, machine learning, and programming languages like Python. Gain experience with AI models such as GPT and learn to craft effective prompts through practice and understanding of model behavior; certifications in AI or data science can also be beneficial.
What are the most commonly searched types of Ai Prompt Engineer jobs in Washington? The most popular types of Ai Prompt Engineer jobs in Washington are:
What job categories do people searching Ai Prompt Engineer Entry Level jobs in Washington look for? The top searched job categories for Ai Prompt Engineer Entry Level jobs in Washington are:
What cities in Washington are hiring for Ai Prompt Engineer Entry Level jobs? Cities in Washington with the most Ai Prompt Engineer Entry Level job openings:
Infographic showing various Ai Prompt Engineer Entry Level job openings in Washington as of August 2026, with employment types broken down into 17% Internship, 49% Full Time, 17% Temporary, and 17% Contract. Highlights an 100% In-person job distribution.

AI Engineer - Financial Services Hybrid

RiskSpan

Washington, DC • On-site, Remote

Contractor

Re-posted 12 days ago


Job description

AI Engineer - Financial Services Remote / Hybrid

About RiskSpan

RiskSpan is a leading source of analytics, modeling, data, and risk management solutions for the Consumer and Institutional Finance industries. We serve banks, issuers of mortgage- and asset-backed securities, asset managers, servicers, and regulators with cutting-edge technology and deep domain expertise across credit, market, and operational risk.

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Position Overview We are seeking a hands-on AI Engineer to design, build, and deploy production-grade AI applications using AWS Bedrock, RAG architectures, and agent-based workflows. This role focuses on building real-world AI systems- chatbots, data analysis agents, and workflow automation solutions, integrating enterprise data and delivering scalable, reliable applications in AWS. The ideal candidate brings strong Python skills, cloud-native engineering experience, and a track record of shipping production AI systems end-to-end.

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Key Responsibilities

Design, build, and deploy AI-powered applications including chatbots, knowledge assistants, and workflow automation agents.

Implement end-to-end solutions covering data ingestion, transformation, prompt orchestration, model interaction, and cloud deployment.

Integrate AI systems with internal APIs, enterprise platforms, and data pipelines.

Design agent workflows with tool/function calling, branching logic, retries, and fallback handling.

Implement human-in-the-loop and approval-based workflows for regulated financial use cases.

Build multi-agent systems for validation, refinement, and complex task decomposition.

Design and implement RAG pipelines covering chunking, embeddings, retrieval, and grounding.

Work with structured and unstructured data using SQL, S3, and data pipeline tools.

Leverage AWS services (S3, Glue, Redshift, Lambda, ECS, Step Functions, SQS/SNS) for storage, transformation, and orchestration.

Monitor and improve AI systems for accuracy, latency, cost, and reliability.

Implement structured output validation, schema enforcement, and guardrails.

Evaluate model performance and iteratively improve grounding and output consistency.

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Required Qualifications

Strong experience building AI applications using LLMs (e.g., AWS Bedrock or equivalent platforms).

Hands-on experience with RAG architectures and retrieval pipelines.

Experience with vector databases, embeddings, and semantic search.

Demonstrated track record deploying production AI systems end-to-end - not just prototypes.

Solid Python programming skills (required).

Experience with core AWS services: Lambda, ECS, S3, Step Functions, SQS/SNS.

Strong SQL skills for querying and integrating structured data.

Experience integrating AI systems with APIs, databases, and cloud services.

Understanding of prompt engineering, tool/function calling, and structured outputs.

Strong problem-solving skills for building reliable systems around probabilistic AI behavior.

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Preferred Qualifications

Experience with AWS Bedrock AgentCore or similar agent orchestration frameworks.

Experience building multi-agent systems or advanced agent workflows.

Experience with AWS Glue, Redshift, EMR, or broader data engineering pipelines.

Experience with LLM evaluation frameworks and automated testing.

Knowledge of schema validation, guardrails, and output control techniques.

Experience with CI/CD, containerization, and infrastructure as code.

Background in financial services, regulated environments, or GSE/enterprise data platforms.

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Why RiskSpan? Join a team that combines deep industry expertise with cutting-edge analytics and AI to solve our clients' most complex challenges. At RiskSpan, we foster innovation, collaboration, and continuous growth.

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Equal Opportunity Employer RiskSpan is proud to be an Equal Opportunity/Affirmative Action employer committed to hiring a diverse workforce and sustaining an inclusive culture. Qualified candidates must be legally authorized to work in the United States on an unrestricted basis.

Employment Type: Contractor