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Assistant Prompt Engineering Jobs Near Me

python developer

Columbus, OH ยท On-site

$47 - $64.75/hr

Prompt Engineering * Retrieval-Augmented Generation (RAG) * TensorFlow or PyTorch (preferred) AWS ... Experience building AI assistants, chatbots, or intelligent automation platforms. * AWS ...

... prompt engineering, connecting chatbot systems to other software applications, supporting ... Assistant using Google CCAI Services, create and utilize Looker Dashboards for performance ...

... assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below) * Set direction for prompt engineering, tool-use patterns, and human-in-the ...

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How much do assistant prompt engineering jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for assistant prompt engineering in the United States is $31.55, according to ZipRecruiter salary data. Most workers in this role earn between $20.19 and $37.98 per hour, depending on experience, location, and employer.
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A map of the United States highlighting the number of Assistant Prompt Engineering job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Assistant Prompt Engineering job openings in each state, with California having the most at 2 and Hawaii the least at 0.

Senior Lead Security Engineer, AI

JPMorganChase

Columbus, OH โ€ข On-site

$110K - $151K/yr

Full-time

Re-posted 11 days ago


Job description

Job Summary:
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers and businesses. As a Senior Lead AI Security Engineer in the Cybersecurity team, you will design and deliver secure AI solutions, drive innovation, and collaborate with cross-functional teams to enhance cybersecurity capabilities.
Responsibilities:
โ€ข Lead end-to-end design and delivery of AI solutions for cyber use cases, from problem framing and data integration to model development, evaluation, deployment, and monitoring.
โ€ข Build secure LLM/RAG services and ML pipelines that integrate with SIEM/XDR, EDR, SOAR, IAM, ITSM, CMDB, code repos, and cloud telemetry.
โ€ข Establish engineering standards for secure AI: prompt security, tool/function calling patterns, input/output validation, PII masking, secrets handling, and deterministic fallbacks.
โ€ข Create evaluation harnesses with offline/online metrics, golden datasets, adversarial prompt sets, jailbreak tests, and safety/quality KPIs.
โ€ข Partner with platform teams to stand up reusable AI components: LLM gateways, vector stores, feature stores, evaluation/observability, and governance workflows.
โ€ข Implement drift and quality monitoring; define SLAs/SLOs; build incident response runbooks for AI-enabled services.
โ€ข Collaborate with risk and MRGR-style governance partners to meet documentation, validation, and attestations; maintain model/AT inventories, monitoring plans, and change logs.
โ€ข Deliver measurable impact: reduce MTTR, improve detection precision, automate control evidence collection, and accelerate secure engineering.
โ€ข Mentor engineers and analysts; publish playbooks, templates, and safe prompt libraries; lead brown-bags and office hours for adoption.
โ€ข Drive a roadmap of 2โ€“3 flagship capabilities per year (e.g., SOC triage assistant, controls automation agent, DevSecOps code copilot).
Qualifications:
Required:
โ€ข Minimum 7 years of software/security engineering, including hands-on experience in one or more of: detection engineering, SecOps, AppSec/DevSecOps, or cloud security.
โ€ข Minimum 3 years building and operating applied ML/LLM systems in production (RAG pipelines, embeddings, fine-tuning/specialization, vector databases, model serving).
โ€ข Proficiency in Python and at least one of: Java, Scala, or TypeScript; experience with microservices, APIs, containers, and Kubernetes.
โ€ข Familiarity with SIEM, EDR, SOAR, IAM, and ITSM integrations; streaming/data engineering with Kafka or similar.
โ€ข Experience with LLM orchestration and guardrails (prompt engineering, injection defense, tool calling, safety filters).
โ€ข Hands-on with ML/LLM ecosystems: PyTorch or TensorFlow; scikit-learn; LangChain/LlamaIndex; ONNX/Triton/Ray.
โ€ข Strong understanding of secure SDLC, privacy, and data protection; ability to partner with governance to meet documentation and monitoring requirements.
โ€ข Demonstrated ability to ship secure, reliable AI features with clear metrics and post-deployment monitoring.
Preferred:
โ€ข Experience building developer copilots for AppSec/DevSecOps (IaC scanning, secrets detection, SAST/DAST triage).
โ€ข Cloud security engineering across one or more major providers; IaC and policy-as-code.
โ€ข Experience or exposure to Cyber operations, Adversarial ML and LLM red teaming experience (prompt injection, data exfiltration, model abuse, poisoning defenses).
โ€ข Graph ML for identity/threat detection; anomaly detection over telemetry.
โ€ข GPU optimization, model quantization/distillation, and on-prem/private model deployment.
โ€ข Familiarity with governance for AI/ML systems in regulated environments.
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutionsโ€”carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.