Today’s List at a Glance
A hand-picked list of top-tier roles for ambitious professionals. Here’s the breakdown:
- 💰 Salary Range: $90,000 – $279,000 a year
- 🏢 Top Companies Hiring: Capital One, Leidos, SAIC
- 📍 Geographic Spread: 8 remote positions, with on-site roles in hubs like Hartford and San Francisco.
- 🪜 Seniority Level: Focus on senior and leadership roles (Principal, Director, Distinguished / senior applied AI engineers).
Featured Applied AI & Prompt Engineering Roles
Principal AI Prompt Engineer at SAIC
📍 Location: Remote (Virginia)
💰 Salary: $120,001 – $160,000 a year
Why it’s a great opportunity: Directly titled AI Prompt Engineer with explicit LLM/prompt responsibilities and a strong senior salary band for remote candidates in Virginia.
Director, Applied AI (Hands-On / Technical) at Leidos
📍 Location: Reston, VA (flexible remote)
💰 Salary: $154,050 – $278,475 a year
Why it’s a great opportunity: Executive-level, hands-on leadership delivering production AI (LLM/RAG/prompting) with a wide compensation band and remote flexibility.
AI Product Engineer at Nerdy Virtual Travel
📍 Location: US-Anywhere (Remote)
💰 Salary: $90,000 – $130,000 a year
Why it’s a great opportunity: Product-focused role owning LLM-driven product lifecycle—ideal for prompt engineers who want product ownership and prototyping responsibility.
Applied AI Engineer at Orbisinternational
📍 Location: US-Anywhere (Remote)
💰 Salary: $120,000 – $160,000 a year
Why it’s a great opportunity: Remote applied AI role focused on designing and deploying LLM-powered applications—well-aligned to advanced prompt engineering and production work.
Our AI Resume Optimizer can help you tailor your resume’s content, section by section, for each of these specific roles.
Applied AI Engineer at Pulsora
📍 Location: US-Anywhere (Remote)
💰 Salary: $90,000 – $130,000 a year
Why it’s a great opportunity: Build and maintain LLM-powered agents and workflows—great for prompt engineers focused on agent prompts and productionization.
Software Engineer Specialist – AI Tools Team at AI2IO
📍 Location: US-Anywhere (Remote)
💰 Salary: $99,000 – $120,000 a year
Why it’s a great opportunity: Work on internal AI tools and prompt/tooling development for LLM workflows—impactful role for engineers building developer platforms for generative AI.
Distinguished AI Engineer (Remote) at Capital One Financial Corporation
📍 Location: US-Anywhere (Remote)
💰 Salary: $244,000 – $279,000 a year
Why it’s a great opportunity: Extremely senior, strategic generative AI engineering role with high compensation—perfect for expert prompt engineers moving into LLM design and governance.
DevOps Engineer at Driver AI Inc
📍 Location: US-Anywhere (Remote)
💰 Salary: $100,000 – $150,000 a year
Why it’s a great opportunity: Focus on AI infrastructure and model deployment—invaluable for prompt engineers who want to bridge prompting with production ML infra.
AI / GenAI Engineer at Prophecy Technologies
📍 Location: Hartford, CT
💰 Salary: $120,000 – $150,000 a year
Why it’s a great opportunity: Generative AI engineering role deploying GenAI/LLM solutions—good match for prompt engineering practice at a solid compensation level.
Applied AI Engineer at Daydream Labs Inc
📍 Location: San Francisco, CA
💰 Salary: $180,000 – $220,000 a year
Why it’s a great opportunity: High-paying applied AI role focused on building scalable LLM-powered systems—appealing to senior prompt engineers driving product-grade generative AI features.
Strategic Playbook for Landing These Roles
Profile of an Ideal Candidate
- Core Responsibility: Design and deliver production-grade LLM and generative-AI solutions—building prompt strategies, retrieval-augmented systems, and inference pipelines that solve product or mission-critical problems.
- Essential Experience: A strong background in applied ML/LLMs, hands-on prompt engineering, and productionizing models (MLOps, model deployment) with demonstrable product or operational outcomes.
- Key Competencies: Beyond technical mastery, these roles demand clear cross-functional communication, product-mindedness, and leadership to translate AI capabilities into measurable business impact.
The Resume Blueprint: Keywords & Metrics
Keywords to Target:
LLM / RAG
Model Deployment
MLOps / Inference Pipelines
Generative AI Product
Metrics that Matter:
✅ Reduced inference latency by 40% through prompt engineering and model-optimization changes, improving user experience and cutting per-request costs.
✅ Delivered an LLM-driven feature that increased task automation by 30%, freeing headcount and accelerating customer workflows.
✅ Scaled a production agent to 100k+ queries/month with >99.9% uptime and measurable accuracy gains after iterative prompt tuning.
Nailing the Narrative: Your Interview Strategy
Be prepared to answer tough, strategic questions. Here are some specific examples:
“Walk us through an end-to-end LLM feature you owned: how you framed the problem, chose the retrieval and prompt strategy, measured success, and iterated post-launch.”
“Describe a time when prompt engineering materially changed a product metric. What experiments did you run, and how did you validate that the change was robust?”
“How have you balanced fidelity, cost, and safety when deploying generative models in production? Give a concrete example of trade-offs you made.”
