AI / GenAI Architect
Cleveland, OH · On-site
... detection, prompt performance, and model quality. • Set up continuous evaluation (CEVAL ... Bot Engineering.
AI / GenAI Architect
Cleveland, OH · On-site
... detection, prompt performance, and model quality. • Set up continuous evaluation (CEVAL ... Bot Engineering.
Bot Detection information
What is a Bot Detection job?
A Bot Detection job involves identifying and mitigating automated bots that engage in fraudulent, malicious, or non-human activities on digital platforms. Professionals in this role use data analysis, machine learning, and behavior-based techniques to differentiate between real users and bots. Their work helps prevent fraud, enhance cybersecurity, and protect businesses from automated threats like account takeovers, spam, and scraping.
What are the key skills and qualifications needed to thrive in the Bot Detection position, and why are they important?
To thrive in Bot Detection, a strong background in cybersecurity, data analysis, and knowledge of machine learning or statistical modeling is essential, typically supported by a degree in computer science, information security, or a related field. Experience with tools such as SIEM platforms, bot mitigation software, scripting languages (like Python), and relevant certifications (e.g., CEH, CISSP) is often preferred. Analytical thinking, attention to detail, and effective communication skills are highly valued soft skills in this role. These abilities are important to identify and respond to sophisticated automated threats, safeguard digital environments, and collaborate effectively with cross-functional security teams.
What are some common challenges faced by professionals working in Bot Detection roles?
Professionals in Bot Detection roles often face the challenge of keeping up with rapidly evolving attack techniques, as cybercriminals continually develop more sophisticated bots to bypass defenses. Staying ahead requires continuous learning, close monitoring of traffic patterns, and swift adaptation of detection strategies. Additionally, balancing the effective blocking of malicious bots while minimizing false positives that could impact real users is a critical aspect of the job. These challenges make the work dynamic and intellectually engaging, and successful bot detection specialists are those who enjoy problem-solving and adapting to new threats.
More about Bot Detection jobs
What are the most commonly searched types of Bot Detection jobs in Ohio? The most popular types of Bot Detection jobs in Ohio are:
What are popular job titles related to Bot Detection jobs in Ohio? For Bot Detection jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Bot Detection jobs in Ohio look for? The top searched job categories for Bot Detection jobs in Ohio are:
What cities in Ohio are hiring for Bot Detection jobs? Cities in Ohio with the most Bot Detection job openings:
Full-time
Posted 12 days ago
Job description
Overview:
Role Summary:
We are looking for a highly experienced AI Architect specializing in Python-based AI development, Large Language Models (LLMs), and the design of chatbots and voice bots. The ideal candidate will architect enterprise-grade conversational AI solutions, ensure robust LLM performance monitoring, and drive innovation in Generative AI systems.
Key Responsibilities
LLM & Conversational AI Architecture
• Architect scalable solutions using LLMs, ChatGPT-style models, and voice AI frameworks.
• Design and build chatbots and voice bots using Python, ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and NLP/LLM pipelines.
• Create frameworks for conversational flows, prompt engineering, retrieval-augmented generation (RAG), and context management.
Solution Development
• Build end-to-end AI applications using Python, integrating with APIs, databases, and cloud-native services.
• Develop modular and reusable components for LLM inference, vector search, embeddings, and model orchestration.
• Integrate LLMs with enterprise systems (CRM, ticketing, case management, internal knowledge bases).
LLM Performance Monitoring & Optimization
• Implement monitoring systems for latency, hallucination rate, safety compliance, drift detection, prompt performance, and model quality.
• Set up continuous evaluation (CEVAL), feedback loops, and telemetry dashboards.
• Optimize inference cost, token usage, model selection (small vs. large models), and caching strategies
Voice Bot & Chat Bot Engineering
• Architect solutions using:
o Speech APIs (Azure Speech, Amazon Transcribe, Google Speech-to-Text)
o Chat platforms (Teams, Slack, web chat widgets)
o Telephony integrations (Twilio, Genesys, Ujet)
• Ensure high accuracy in intent detection, slot filling, sentiment tracking, and multimodal interaction.
MLOps & Deployment
• Implement MLOps practices including CI/CD, model versioning, A/B testing, evaluation pipelines, and governance.
• Deploy models on cloud platforms such as Azure, AWS, or GCP (Azure preferred if using OpenAI/Azure OpenAI).
Ensure compliance with enterprise AI governance, security, and ethical AI standards
Essential Skills: AI Architect| Python| LLM| Conversational AI Architecture| voice AI frameworks| ASR (Automatic Speech Recognition) | TTS (Text-to-Speech) | and NLPLLM pipelines| Voice Bot Chat Bot Engineering.
Role Summary:
We are looking for a highly experienced AI Architect specializing in Python-based AI development, Large Language Models (LLMs), and the design of chatbots and voice bots. The ideal candidate will architect enterprise-grade conversational AI solutions, ensure robust LLM performance monitoring, and drive innovation in Generative AI systems.
Key Responsibilities
LLM & Conversational AI Architecture
• Architect scalable solutions using LLMs, ChatGPT-style models, and voice AI frameworks.
• Design and build chatbots and voice bots using Python, ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and NLP/LLM pipelines.
• Create frameworks for conversational flows, prompt engineering, retrieval-augmented generation (RAG), and context management.
Solution Development
• Build end-to-end AI applications using Python, integrating with APIs, databases, and cloud-native services.
• Develop modular and reusable components for LLM inference, vector search, embeddings, and model orchestration.
• Integrate LLMs with enterprise systems (CRM, ticketing, case management, internal knowledge bases).
LLM Performance Monitoring & Optimization
• Implement monitoring systems for latency, hallucination rate, safety compliance, drift detection, prompt performance, and model quality.
• Set up continuous evaluation (CEVAL), feedback loops, and telemetry dashboards.
• Optimize inference cost, token usage, model selection (small vs. large models), and caching strategies
Voice Bot & Chat Bot Engineering
• Architect solutions using:
o Speech APIs (Azure Speech, Amazon Transcribe, Google Speech-to-Text)
o Chat platforms (Teams, Slack, web chat widgets)
o Telephony integrations (Twilio, Genesys, Ujet)
• Ensure high accuracy in intent detection, slot filling, sentiment tracking, and multimodal interaction.
MLOps & Deployment
• Implement MLOps practices including CI/CD, model versioning, A/B testing, evaluation pipelines, and governance.
• Deploy models on cloud platforms such as Azure, AWS, or GCP (Azure preferred if using OpenAI/Azure OpenAI).
Ensure compliance with enterprise AI governance, security, and ethical AI standards
Essential Skills: AI Architect| Python| LLM| Conversational AI Architecture| voice AI frameworks| ASR (Automatic Speech Recognition) | TTS (Text-to-Speech) | and NLPLLM pipelines| Voice Bot Chat Bot Engineering.
About Purple Drive Technologies
Sourced by ZipRecruiter
Industry
It services
Company size
51 - 200 Employees
Headquarters location
Irvine, CA, US
Year founded
2016