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Director Ai Prompt Engineer Jobs in Indiana (NOW HIRING)

... AI techniques enhancing LLMs - Experience in prompt engineering for LLM outputs - Developing ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

New

$51.75 - $68.50/hr

... to the Director, to IT team, and to the implementation partner. This role requires someone who ... Produce adoption aids and internal tooling including prompt guides, workflow reference materials ...

ERP AI Engineer - Manager

Indianapolis, IN ยท On-site

$99K - $232K/yr

... and prompt engineering - Building scalable, cloud-native microservices and containerized ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

Understanding of prompt engineering, retrieval-based AI systems, and agent design concepts ... direct and indirect subsidiaries, Merchants Bank of Indiana, Merchants Capital Corp., Merchants ...

AI DevSecOps Senior Engineer

Indianapolis, IN ยท Hybrid

$109K - $150K/yr

AI DevSecOps Senior Engineer Locations: This role requires associates to be in-office 1-2 days per ... Familiarity with AI security risks (e.g., OWASP Top 10 for LLMs, prompt injection, data leakage)

Showing results 41-60

Director Ai Prompt Engineer information

What is a Director AI Prompt Engineer?

A Director AI Prompt Engineer is a senior leadership role responsible for overseeing teams that design, develop, and optimize prompts for AI language models. This position combines deep understanding of artificial intelligence, natural language processing, and strategic management to ensure that AI systems generate high-quality, accurate, and safe outputs. The director sets the vision for prompt engineering, collaborates with cross-functional teams, and ensures alignment with organizational goals. Their work is crucial for advancing AI capabilities and maintaining ethical standards in AI interactions.

What are the key skills and qualifications needed to thrive as a Director AI Prompt Engineer?

To thrive as a Director AI Prompt Engineer, you need deep expertise in AI/ML technologies, prompt engineering, natural language processing, and leadership experience, often backed by an advanced degree in a technical field. Familiarity with AI platforms (like OpenAI, Google Cloud AI), programming languages (such as Python), and workflow management tools is crucial, as are certifications in machine learning or data science. Outstanding communication, strategic thinking, and team leadership are essential soft skills to guide multidisciplinary teams and align AI solutions with business goals. These qualifications ensure the effective design, deployment, and management of AI systems that drive innovation and organizational success.

What are the primary challenges faced by a Director AI Prompt Engineer when leading prompt engineering teams?

A Director AI Prompt Engineer often navigates challenges such as aligning prompt engineering strategies with organizational goals, ensuring prompt quality and consistency across diverse projects, and keeping the team updated with advances in AI language models. Additionally, effective collaboration with data scientists, product managers, and engineering teams is crucial for integrating prompt solutions into products. Balancing technical leadership with mentoring and professional development for prompt engineers is also a key responsibility in this role.

What is the difference between Director Ai Prompt Engineer vs AI Content Strategist?

AspectDirector Ai Prompt EngineerAI Content Strategist
Required CredentialsExperience in AI, machine learning, prompt engineering, and related certificationsBackground in marketing, content creation, SEO, and digital strategy
Work EnvironmentTech companies, AI labs, or digital agencies focusing on AI developmentMarketing agencies, media firms, or corporate marketing departments
Employer & Industry UsagePrimarily in AI and tech industriesAcross marketing, advertising, and media sectors
Search & Comparison IntentUnderstanding roles in AI prompt engineeringComparing AI-driven content planning roles

The main difference is that a Director Ai Prompt Engineer focuses on designing and optimizing AI prompts for machine learning models, often requiring technical expertise in AI and programming. An AI Content Strategist concentrates on planning and managing content strategies using AI tools to enhance marketing efforts. Both roles involve AI but serve different functions within the industry.

Are AI prompt engineers in demand?

AI prompt engineers are increasingly in demand as organizations seek to optimize interactions with large language models and AI systems. The role requires skills in natural language processing, machine learning, and familiarity with AI tools, making it a growing field with strong job prospects.

What are the most commonly searched types of Ai Prompt Engineer jobs in Indiana?

The most popular types of Ai Prompt Engineer jobs in Indiana are:

What are popular job titles related to Director Ai Prompt Engineer jobs in Indiana?

For Director Ai Prompt Engineer jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Director Ai Prompt Engineer jobs in Indiana look for?

The top searched job categories for Director Ai Prompt Engineer jobs in Indiana are:

What cities in Indiana are hiring for Director Ai Prompt Engineer jobs?

Cities in Indiana with the most Director Ai Prompt Engineer job openings:

AI DevOps. Engineer

Expedient Holdings USA, LLC

Indianapolis, IN โ€ข On-site

$120 - $150/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


Job description

Join Expedient's AI CTRL product team as our AI DevOps Engineerโ€” a senior, handsโ€‘on engineer who will build the framework that manages, configures and ships agentic workflows, tooling applications, and AI integrations to clients quickly, safely, and repeatably.

Youโ€™ll own the path from commit to production: Gitโ€‘driven CI/CD, infrastructure as code, release and config management, observability, and the LLMOps practices that keep modelโ€‘powered systems reliable and costโ€‘efficient. This is a build roleโ€”you wonโ€™t be maintaining someone elseโ€™s pipelines; youโ€™ll be creating the framework the AI Dev team builds on.

What Youโ€™ll Do:
  • CI/CD Pipelines: Design and build Gitโ€‘based pipelines that automate build โ†’ test โ†’ deploy for Retool apps, agentic workflows, MCP servers, and data connectorsโ€”turning manual client deployments into repeatable, gated releases.
  • Infrastructure as Code: Make the platform reproducible. Use Terraform, Helm, and GitOps (ArgoCD/Flux) to provision and manage Kubernetes (Nutanix NKP) clusters and perโ€‘client environments as code.
  • Configuration Management: Manage environment and deployment configuration as code across a growing fleet of client deploymentsโ€”eliminate config drift and oneโ€‘off manual changes.
  • Release Management: Own versioning, environment promotion, release gates, and clean rollback. Maintain versioned, deployable artifacts so any release can be reproduced or reverted.
  • Observability & Tracing: Build the monitoring backboneโ€”Elastic/ECK, APM, and telemetry distributed tracingโ€”with deployment health, SLOs/SLIs, and usage/cost instrumentation across all client deployments. Strengthen alerting so issues surface before clients feel them.
  • LLMOps Practices: Stand up prompt and configuration versioning, model/prompt evaluation pipelines, A/B testing of prompts and models, multiโ€‘provider traffic routing and failover, and token/cost dashboardsโ€”the AIโ€‘specific discipline that keeps modelโ€‘powered systems accurate, available, and affordable.
  • Change & Risk Management (incl. Compliance): Implement controlledโ€‘change processesโ€”approvals, audit trails, and guardrailsโ€”with complianceโ€‘asโ€‘code for SOC 2 audit logging, secrets management (e.g., vaults/sealedโ€‘secrets), and SSO/OIDC configuration.
  • Automation Marketplace: Build an internal library of vetted, reusable workflows, connectors, and IaC modules that accelerate client deliveryโ€”and graduate proven items into a clientโ€‘facing catalog aligned to the Agentic Workflow Engine (AWE).
  • Collaborate & Document: Partner with the AI Dev engineering team on platform standards; write runbooks, release guides, and architecture docs that let the framework scale beyond.
What Weโ€™re Looking For:
  • Experience: 3โ€“5 years in DevOps, platform engineering, site reliability, or MLOps/LLMOps. Prior experience at a managed service provider, SaaS company, or enterprise technology team is a strong plus.
  • Gitโ€‘based CI/CD: Designing automated build/test/deploy pipelines from scratch.
  • Infrastructure as Code: Terraform and Helm; GitOps with ArgoCD or Flux.
  • Kubernetes: Operating and automating clusters (Nutanix NKP or equivalent); namespaces, workloads, container lifecycle.
  • Observability: Elastic/ECK, APM, OpenTelemetry tracing; defining alerts, SLOs/SLIs (Prometheus/Grafana experience transfers).
  • Scripting & data: Strong Python and Bash; SQL fundamentals.
  • Secrets & identity: Secrets management (Vault or equivalent), SSO/OIDC configuration (Entra ID, Okta, OneLogin).
  • Workflow orchestration: Argo Workflows, Airflow, or similar (a plus).
  • LLM APIs: Working familiarity with Anthropic Claude, OpenAI, and/or Google Geminiโ€”prompt construction, tool use/function calling, token management.
  • RAG & MCP awareness: Chunking, embedding, vector search, contextโ€‘window management; Model Context Protocol integrations (a plus).
  • Compliance exposure: SOC 2 audit logging and controlsโ€‘asโ€‘code (a plus).
  • Builder mindset: Sees a manual process and automates it; ships the framework, not just the fix.
  • Automationโ€‘first & reliabilityโ€‘minded: Treats infrastructure, config, and compliance as code; thinks in SLOs, blast radius, and rollback.
  • Documentation instinct: Writes the runbook before calling something done; updates the guide when the process changes.
  • Riskโ€‘aware: Balances deployment velocity with controlled change and auditability.
  • Selfโ€‘directed, strong ownership mentality, excellent communicator, thrives in a fastโ€‘paced environment.
  • Education: Bachelorโ€™s in Computer Science, Engineering, Information Systems, or related field (or equivalent practical experience).
Location & Compensation:

Indianapolis, Cleveland, or Pittsburgh. Hybrid work model. Regional travel may be required.

Salary for this position is directly related to your own experience, knowledge, and skills. Estimated range for this role is $120,000 to $150,000.

Working for Expedient

We prioritize ongoing education and continuous innovation to remain at the forefront of the information technology landscape. Our commitment to learning is reflected in our comprehensive employee training and tuition reimbursement programs, which are driven by our employees and funded by Expedient 100%.

For our fullโ€‘time employees we offer an exceptional benefits package including three weeks of paid time off annually that increases with tenure plus your birthday off and a health holiday to be used for preventive care. We offer parental leave, topโ€‘tier medical, dental, and vision, disability and life insurance, at an affordable rate, wellness engagement opportunities, and a 401(k) with a generous match.

We also recognize the importance of a comfortable and convenient work environment. We offer a hybrid work model for many roles, paid parking and other perks.

Expedient is an equal opportunity employer. Qualified applicants will receive fair and equitable consideration for employment without regard to their race, color, religion, national origin, gender, protected veteran status, disability, or any other characteristic protected by law.

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