Automation Engineer, Agentic Orchestration at StackAdapt
United States, , USA -
Full Time


Start Date

Immediate

Expiry Date

28 Nov, 25

Salary

0.0

Posted On

28 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Computer Science, Pandas, Rest, Json, Information Technology, Design Principles, Business Process Analysis, Natural Language Processing, Nlp, Rpc, Sse, Ethnicity, Automation, Python, Graphql

Industry

Information Technology/IT

Description

StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.
An Automation Engineer with a focus on Agentic Orchestration focuses on seamlessly connecting AI capabilities, including orchestrated agent systems, with existing business processes and enterprise applications. This role will leverage modern AI tools and frameworks to build sophisticated automation solutions and create and configure AI agents to handle complex, non-repetitive tasks that require reasoning, context-awareness, and interaction with multiple systems. Our ultimate goal is to design and deploy autonomous agentic systems that can independently manage and execute complex business processes with a high degree of accuracy and efficiency.

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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