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Artificial Intelligence Engineer

Job in City of Rochester, Rochester, Monroe County, New York, 14602, USA
Listing for: Mindex
Full Time position
Listed on 2026-01-01
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 90000 USD Yearly USD 90000.00 YEAR
Job Description & How to Apply Below
Location: City of Rochester

Artificial Intelligence Engineer - Mindex

Artificial Intelligence Engineer at Mindex

Founded in 1994 and celebrating 30 years in business, Mindex is a software development company with a rich history of demonstrated software and product development success. We specialize in agile software development, cloud professional services, and creating our own innovative products. We are proud to be recognized as the #1 Software Developer in the 2023 RBJ's Book of Lists and ranked 27th in Rochester Chamber’s Top 100 Companies.

Additionally, we have maintained our certification as a Great Place to Work for consecutive years in a row. Our list of satisfied clients and #ROCstar employees are both rapidly growing— Are you next to join our team?

Mindex’s Software Development division is the go-to software developer for enterprise organizations looking to engage teams of skilled technical resources to help them plan, navigate, and execute through the full software development lifecycle.

We seek a skilled Senior AI Conversation Engineer to join our team.

Base pay range

$90,000.00/yr - $/yr

Essential Functions

The Senior AI Conversation Engineer will design, architect, and implement robust conversational AI systems (chatbots, voice assistants, or virtual agents) that drive real business value across enterprise systems, with extensive use of Python, SQL, and modern data engineering frameworks.

Key Responsibilities
  • Define conversation flows and dialogue architectures to support multi-turn, context-aware, natural dialogs.
  • Develop, write, and optimize prompts to guide large-language models (LLMs) or other generative models toward accurate, context-appropriate, safe outputs.
  • Fine-tune and/or adjust models (when applicable), including prompt tuning, fine-tuning, or parameter optimization, to align model behavior with product and user goals.
  • Integrate conversational AI with existing backend systems via APIs and data pipelines; ensure seamless data flow, context handling, and retrieval when needed.
  • Iterate on conversation design through testing: run A/B tests, user simulations, evaluate model outputs (with both automated metrics and human review), debug edge cases, and improve performance over time.
  • Collaborate closely with product managers, UX / conversation designers, data engineers, and other stakeholders to define requirements, ensure ethical and safe model behavior, and deliver polished user experiences.
Requirements
  • Bachelor’s Degree in Computer Science or equivalent experience preferred.
  • 5 plus years of experience in software engineering with a strong focus on Python development and strong problem-solving skills.
  • Demonstrated experience in conversation architecture / design: defining dialogue flows, state/context management, branching logic, user experience considerations in conversational UI.
  • Deep expertise in prompt engineering: writing, testing, and refining prompts to guide large language or generative models toward desired behavior, leveraging techniques like few-shot, zero-shot prompting, chain-of-thought, role prompting, or context conditioning.
  • Experience with model tuning (prompt tuning, fine-tuning, hyperparameter adjustment) or otherwise optimizing model outputs to meet quality, safety, and reliability standards.
  • Practical experience with at least one conversation / agent platform (e.g. Dialogflow preferred; or other chatbot/voice-bot platforms / agent frameworks). Ability to build, deploy, and maintain agents on such platforms.
  • Experience with API integration; connecting the conversational agent to backend services, databases, or external APIs to fetch or store context, user data, or dynamic content.
  • Solid conversation design experience; understanding of user-centered design, usability, natural language understanding / generation, user experience (UX) considerations, tone and style, context management, fallback and error handling.
  • Strong communication skills, ability to collaborate across disciplines (product, design, engineering, data), and translate technical AI capabilities into user-facing solutions.
  • Curiosity about latest developments in AI / NLP / LLMs, willingness to experiment, learn, and refine prompts / models…
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