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Manager Prompt Engineering Jobs in Indiana (NOW HIRING)

Lead Forward Deployed Engineer - AWS

Indianapolis, IN ยท On-site

$98K - $129K/yr

... feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management * Experience integrating LLM ...

$51.75 - $68.50/hr

... managers * Prototype rapid AI and automation proofs-of-concept for stakeholder review, with a ... Demonstrated experience with LLM APIs, prompt engineering, or AI agent frameworks - you have built ...

Identify high-value AI use cases and guide teams on prompt engineering, model selection, and model ... Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong ...

Software Engineer, Backend

Indianapolis, IN ยท On-site

$152K - $219K/yr

Database Management: Experience designing and querying relational databases using SQL (PostgreSQL ... Able to comment on the difference between 'prompt engineering', 'context engineering', and 'agentic ...

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Manager Prompt Engineering information

What is a Manager of Prompt Engineering?

A Manager of Prompt Engineering is a professional who leads teams focused on designing, developing, and optimizing prompts for artificial intelligence models, particularly large language models (LLMs) like ChatGPT. They oversee the creation of effective prompts to ensure AI systems provide accurate, relevant, and safe responses. This role involves collaborating with data scientists, engineers, and product managers, as well as setting best practices for prompt creation and evaluation. Additionally, they may be responsible for training team members and implementing strategies to improve prompt performance over time.

What are the key skills and qualifications needed to thrive as a Manager of Prompt Engineering, and why are they important?

To thrive as a Manager of Prompt Engineering, you need expertise in natural language processing, AI model deployment, and prompt design, typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), prompt engineering platforms, and version control systems is expected, along with experience managing technical teams. Strong leadership, problem-solving, and communication skills distinguish top performers in this role. These abilities are crucial for ensuring effective AI solutions, driving team productivity, and aligning prompt engineering initiatives with organizational goals.

How does a Manager of Prompt Engineering typically collaborate with cross-functional teams to optimize AI outputs?

As a Manager of Prompt Engineering, you will frequently collaborate with data scientists, software engineers, product managers, and UX designers to refine and optimize prompt strategies for AI models. This involves translating business requirements into effective prompt templates, conducting prompt experiments, and communicating findings to stakeholders. Regular cross-functional meetings and feedback sessions are common, ensuring that the AI outputs align with both technical capabilities and user needs. Building strong relationships across teams is essential for successfully iterating on prompt designs and deploying scalable solutions.
What are the most commonly searched types of Prompt Engineering jobs in Indiana? The most popular types of Prompt Engineering jobs in Indiana are:
What cities in Indiana are hiring for Manager Prompt Engineering jobs? Cities in Indiana with the most Manager Prompt Engineering job openings:
Instructional Design Program Manager

Instructional Design Program Manager

Relativity

Indianapolis, IN โ€ข On-site

Other

Posted 6 days ago

New


Job description

Posting Type

Remote

Job Overview

The Instructional Design Program Manager is a senior practitioner who designs, scales, and continuously improves learning programs that drive customer adoption, accelerate time-to-value, and deliver measurable business impact. This role is for someone who applies generative AI and agentic workflows as practical tools in how learning gets built, personalized, and improved-not just experimentation.
At this level, you operate at the intersection of learning strategy, AI-augmented development, and program execution. You bring a strong point of view on instructional design practice, contribute to where the function is going, and apply that thinking consistently in your work.

Job Description and Requirements

Program and Strategic Leadership

  • Own one or more instructional design programs or portfolios from intake through measurement and iteration, treating them as living systems rather than project deliverables.

  • Translate business priorities into outcome-based learning strategies with clear roadmaps and defined success metrics tied to adoption, efficiency, and customer impact.

  • Use AI-assisted data synthesis, learner signals, and performance analytics to make faster, better-informed trade-off recommendations across scope, timeline, and resources.

  • Identifyand surface opportunities to expand program value through intelligent content reuse, automated personalization, and adaptive delivery.

AI-Augmented Design and Systems Thinking

  • Build learning programs with generative AI as a corecomponent, applying LLM-assisted content development, automated localization, intelligent content refresh, and AI-driven quality review as standard practice.

  • Design and implement agentic workflows that reduce manual effort in content creation, SME review cycles, translation, accessibility remediation, and learner support.

  • Build modular, prompt-driven content systems where generative AI can extend, update, and personalize assets at scale without proportional human effort.

  • Evaluate emerging AI tools, agents, and platforms and provide recommendations using a clear framework for responsible use, output quality, andbiasmitigation.

  • Apply and uphold governance practices for AI-generated learning content, includingreviewcheckpoints, accuracy standards, and transparency with learners.

Instructional Design Leadership

  • Advance modern instructional design practice, including AI-assisted authoring, dynamic content models, and agent-supported learner experiences such as on-demand coaching, simulated practice, and intelligent job aids.

  • Ensure all learning solutions are workflow-aligned, outcome-oriented, and designed for real customer contexts rather than generic skill coverage.

  • Apply and help evolve design standards that improve quality, efficiency, and reuse, and that are compatible with AI-assisted development pipelines.

  • Review and provide input on high-impact learning solutions to ensure they are scalable, effective, and responsibly built.

  • Mentor instructional designers on prompt engineering, AI toolselection, responsible generation practices, and the evolving boundaries of human vs. AI authorship.

Execution and Delivery

  • Lead the shift from manual, course-based production to AI-assisted, modular, continuously evolving learning ecosystems within your program portfolio.

  • Use agentic tools to automate repeatable tasks: content audits, gap analysis, metadata tagging, assessment generation, and personalization logic.

  • Improve discoverability and learner experience through AI-powered content recommendations, adaptive learning paths, and conversational learning interfaces.

  • Partner with subject matter experts using AI-assisted interview and synthesis workflows to accelerate knowledge capture without sacrificing depth or accuracy.

  • Use learner behavior data,completionsignals, and AI-generated insights to continuously refine programs.

Stakeholder Partnership and Influence

  • Partner cross-functionally to align learning investment to business priorities, with a clear AI strategy narrative for senior audiences.

  • Provide well-reasoned recommendations on what gets built, how it is delivered, and where AI can close gaps faster than traditional development.

  • Serve as atrustedvoice on the responsible use of generative AI in learning, including what it can and cannot do well, and how to communicate that to stakeholders and learners.

  • Representthe Customer Education function as a driver of adoption, efficiency, and growth.

Qualifications and Experience

  • Deepexpertisein instructional design, adult learning theory, and assessment, applied at a program or portfolio level.

  • Demonstrated hands-on experience using generative AI tools (such as Claude, ChatGPT, Gemini, or similar) in real instructional design workflows, not just experimentation.

  • Experience designing or implementing agentic workflows that automate meaningful parts of the content development or learner support lifecycle.

  • Strong ability to connect learning programs to business outcomes and evaluate ROI with rigor.

  • Track recordof improving scalability, efficiency, or innovation in learning programs through systems thinking.

  • Excellent communication and stakeholder management skills, including the ability to present AI strategy and responsible use clearlytosenior leaders.

  • Proven ability to mentor instructional designers on both craft and emerging technology.

  • Strong program management skills: prioritization, risk management, and delivery in fast-moving environments.

  • Proficiencywith LMS platforms, modern authoring tools, and AI-powered content development platforms.

  • Comfortoperatingin ambiguity and evolving practice as the technology landscape shifts.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$92,000 and $138,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Adult Learning Theory, Content Development, Curriculum Development, Instructional Design, Learning Management, Learning Management Systems (LMS), Learning Theory, Performance Improvements, Program Management, Training Delivery