Jobs via Dice ยท 3 days ago
Senior GenAI Engineer Architect at Dallas, Atlanta, Chicago, SFO and Seattle
Dallas, TX
Full-time
Onsite
Senior LevelDice is the leading career destination for tech experts at every stage of their careers. Our client, MethodHub, is seeking a creative and innovative Senior GenAI Engineer Architect/Data Scientist to develop cutting-edge custom GEN AI solutions and predictive AI models, driving the integration of AI technologies across business operations.
Computer Software
Responsibilities
Design, develop, and implement both generative and predictive AI models (including NLP, computer vision, etc)
Lead the development of innovative solutions such as intelligent autonomous agents for complex tasks and multimodal interactions
Integrate agentic workflows that utilize AI agents to automate tasks and improve operational efficiency
Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to align AI solutions with business objectives
Demonstrates proficiency in API architecture and design to develop custom generative AI applications built with external interfacing, traffic control, runtime execution of business logic, data access, authentication, and deployment components
Work with cloud platforms (e.g., Azure, AWS, Google Cloud Platform) and big data tools (e.g., Databricks, PySpark) to develop AI solutions
Optimize AI models and algorithms for performance, scalability, and efficiency
Ensure the security and compliance of AI solutions, adhering to best practices and regulations
Implement monitoring and logging mechanisms to track performance, reliability, and usage of AI solutions
Work closely with DevOps and IT teams to deploy AI models into production environments, ensuring scalability, performance, and optimization
Monitor and troubleshoot deployed models and pipelines for optimal performance
Design and maintain data pipelines for efficient data collection, processing, and storage (e.g., data lakes, data warehouses)
Create comprehensive documentation for deployment processes and provide training to relevant teams to ensure proper model management
Conduct research to stay at the forefront of emerging AI techniques, tools, and trends
Integrate new AI tools and methodologies into existing business processes and applications
Lead the development of private GenAI tools, including LLMs and specialized AI use cases
Collaborate with cross-functional teams to align AI projects with business requirements and strategic goals
Lead and contribute to GenAI and AI business development efforts such as capability pitches, demos, proposals, and overall project planning
Communicate complex AI concepts and results to non-technical stakeholders
Lead and mentor a small team of junior engineers and data scientists
Qualification
Required
Demonstrated excellence in Agentic AI architecture, encompassing development, testing, and research of GenAI agents, utilizing current-generation deployments and pioneering next-generation patterns and research
Skilled in constructing agentic systems through techniques such as multi-agent systems, reinforcement learning, dynamic workflows, caching/memory management, and concurrent orchestration
Proficient in various AI and Agentic AI frameworks, including LangChain/LangGraph, Crew AI, Semantic Kernel or Open AI Agentic SDK
Strong skills in prompt engineering and its techniques including design, development, and refinement of prompts (zero-shot, few-shot, and chain-of-thought approaches) to maximize accuracy and leverage optimization tools
Proficiency in programming languages such as Python and SQL, as well as machine learning libraries like TensorFlow, PyTorch, and scikit-learn
Proficiency in URLs and API Endpoints, HTTP Requests, Authentication Methods, Response Types, JSON/REST, Parameters and Data Filtering, Error Handling, Debugging, Rate Limits, Tokens, Integration, and Documentation
Experience with cloud platforms (e.g., AWS, Azure) and big data tools (e.g., Databricks, PySpark)
Knowledge of deployment tools (e.g., Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy)
Strong understanding of data engineering principles, including experience with SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis)
Company
Jobs via Dice
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0-1 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase