AI Prompt Engineer

Role : . AI Prompt Engineer
Location: Chandler, AZ, Jersy City, NJ & Charlotte, NC
FTE

Job Description

Must Have Technical/Functional Skills

Objective of Role:
We are seeking a highly skilled Prompt Engineering & AI Solutions Specialist to design, develop, and optimize enterprise-grade AI solutions using frontier large language models (LLMs). The ideal candidate will have hands-on experience with Microsoft Copilot Studio, Azure OpenAI, and advanced prompt engineering techniques to build secure, scalable, and compliant AI-powered assistants and workflows for banking and financial services use cases.

This role will work closely with product owners, architects, risk/compliance teams, and business stakeholders to operationalize Generative AI across infrastructure, operations, and business functions.

Primary Skill

• Strong hands-on experience with Microsoft Copilot Studio.

• Proven experience using Azure OpenAI / OpenAI APIs.

• Practical experience with frontier LLMs (GPT 4 class or equivalent).

• Solid understanding of prompt engineering frameworks and design patterns.

• Hands-on experience with RAG architectures and vector search technologies.

• Strong knowledge of tokenization, context windows, and inference latency tradeoffs.

• Proficiency in Python for AI integration and automation.

• Experience working with REST APIs, JSON, and YAML.
• Experience with cloud platforms, preferably Microsoft Azure.

• Familiarity with AI governance, Responsible AI, and model risk management.

• Prior experience delivering enterprise copilots or chatbots at scale.

Secondary / Nice to Have Skills

• Experience with Power Platform (Power Apps, Power Automate).

• Exposure to model evaluation, monitoring, and AI observability tools.

• Knowledge of AI ethics and regulatory expectations in BFSI environments.

Experience:

Minimum 6+ years

Roles & Responsibilities

• Design, test, and refine advanced system, user, and tool prompts for frontier LLMs (GPT-4/4.1 class).

• Apply prompt engineering patterns including few-shot, zero-shot, ReAct, and controlled chain-of-thought.

• Implement Retrieval-Augmented Generation (RAG) using vector search and enterprise knowledge sources.

• Continuously optimize prompts for accuracy, consistency, latency, and cost efficiency.

• Build and deploy AI assistants using Microsoft Copilot Studio.

• Integrate copilots with enterprise APIs, workflows, and data sources.

• Implement responsible AI controls including content filtering, grounding, and hallucination reduction.

• Enforce data privacy, PII masking, and access control in AI workflows.

• Collaborate with Risk, Legal, and Compliance teams to meet regulatory and audit requirements.

• Support model governance, SDLC compliance, and production readiness reviews.

• Document prompt frameworks, AI workflows, and operational standards.