Automation Engineer, Agentic Orchestration
New
S
StackAdaptMarketing Technology
Canada; United StatesFull-Time
Salary not disclosed
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Job Details
- Required Skills
- PythonMachine LearningNLPLLMLangChain
Requirements
- Demonstrable experience with AI services from major cloud providers (e.g., OpenAI, Google Vertex AI, AWS Bedrock).
- Hands-on experience with LLM APIs.
- Solid understanding of business process analysis and re-engineering.
- Solid understanding of Natural Language Processing (NLP), LLMs, and ML principles.
- Experience with enterprise integration platforms (e.g., Workato, MuleSoft, Boomi).
- Hands-on experience with conversational AI platforms and frameworks.
- Proficiency in Python and its associated AI/ML libraries (e.g., LangChain, LlamaIndex, Pandas, TensorFlow, or PyTorch).
- Solid understanding of embedding processes, vector databases, RAG systems and knowledge graphs.
- Strong understanding of API design principles (REST, RPC, SSE, GraphQL) and data formats (JSON, XML).
- Familiarity with database technologies (SQL and NoSQL).
- Bachelor's degree in Computer Science, Information Technology, or equivalent practical experience.
Responsibilities
- Collaborate with business stakeholders to conduct in-depth analysis of existing workflows, identifying and documenting opportunities for intelligent, AI-driven automation.
- Oversee the entire lifecycle of AI agent development, from initial design and prototyping to testing, deployment, configuration, and lifecycle of AI solutions in production.
- Ensure AI agent development security, scalability, and reliability through ongoing monitoring and performance tuning.
- Design and implement integration solutions to connect AI agents and models with enterprise systems such as CRMs, ERPs, and internal databases.
- Design and implement an evaluation system that serves as a mechanism for quality control and continuous improvement.
- Build and configure AI agents to perform tasks such as natural language understanding, data extraction, decision-making, and system interactions.
- Develop custom connectors, APIs, and middleware to facilitate data exchange and process automation between AI services and other applications.
- Continuously explore and evaluate new AI technologies and tools to drive innovation in automation.
- Mentor system admins and junior developers to build and configure AI Agents.
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