Role: AI Prompt Engineer
Location: Chandler, AZ Jersey City, NJ Charlotte, NC
Hire Type: Full Time
Note: F2F Interview is Mandatory
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.
