Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Automation Engineer, Agentic Orchestration
- Salary
- USD 128k–176k / yr
- Department
- Software Engineering
- Employment
- Full Time
- Experience
- Entry-Level, Junior
- Published
- Apply before
- 4 Dec 2026
- Listing views
- 32
- Application actions
- 2
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About this role.
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.
What We’re Looking For:
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.
What you’ll be doing:
- 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.
What you’ll bring to the table:
- Demonstrable experience with AI services from major cloud providers (e.g., OpenAI, Google Vertex AI, AWS Bedrock) and hands-on experience with LLM APIs.
- A 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).Experience with RPA platforms (e.g., UiPath, Automation Anywhere, Blue Prism) is a plus, but the focus is on modern AI-driven automation.
- Hands-on experience with conversational AI platforms and frameworks for building chatbots and virtual assistants.
- Proficiency in Python and its associated AI/ML libraries (e.g., LangChain, LlamaIndex, Pandas, TensorFlow, or PyTorch).
- A 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).A creative and analytical mindset with passion for solving complex problems through automation.
- Entrepreneurial approach, strong builder with excellent problem-solving skills and the ability to work effectively in a cross-functional team.
- Bachelor’s degree in Computer Science, Information Technology, or equivalent practical experience.
The compensation range listed for this role reflects the expected base salary for candidates located in the posting country based on a global rate. It is informed by market data and the approved budget for this position. StackAdapt maintains different compensation ranges for roles across other countries and regions, and final offers will be aligned to the candidate’s current location. We do not ask candidates about current or prior salary history, and we will not use such information, if volunteered, in setting an offer.
This range represents base salary only. Depending on the role, candidates may also be eligible for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package.
Factors Influencing Final Compensation:
- The final compensation offer will be determined by a variety of factors, which may include, but are not limited to: the candidate’s specific experience, technical skills, knowledge, abilities, and relevant education, licensure, and certifications.
- Other business factors, such as organizational needs and budget alignment, may also be considered in the final offer.
Canada Base Salary Band
$140,000—$192,500 CAD
USA Base Salary Band
$128,000—$176,000 USD
StackAdapter’s Enjoy:
- Highly competitive salary
- Retirement/ 401K/ Pension Savings globally
- Competitive Paid time off packages including birthday’s off!
- Access to a comprehensive mental health care program
- Health benefits from day one of employment
- Work from home reimbursements
- Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto
- Robust training and onboarding program
- Coverage and support of personal development initiatives (conferences, courses, books etc)
- Access to StackAdapt programmatic courses and certifications to support continuous learning
- An awesome parental leave program
- A friendly, welcoming, and supportive culture
- Our social and team events!
Please note: Benefits and perks may vary depending on your country of employment and the nature of your engagement. In locations where StackAdapt does not have a legal entity, employment and benefits are administered in accordance with local regulations and partner policies.
StackAdapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability, superpower status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt.
StackAdapt is committed to providing an inclusive and accessible recruitment process. Accommodations are available upon request for candidates taking part in all aspects of the selection process. If you require an accommodation, please let us know.
We use artificial intelligence (AI) to streamline the resume reviews of candidates and assess their fit based on the criteria outlined in the job posting. We do not use AI to make any final hiring or interview decisions.
About StackAdapt
We’ve been recognized for our diverse and supportive workplace, high performing campaigns, award-winning customer service, and innovation. We’ve been awarded:
G2 Top Software for 2026
2026 Best Workplaces™ for Young Talent and in Canada by Great Place to Work®
#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising
2026 Winner in the (CTV/OTT) Product/Platform category for the 2026 ADWEEK Tech Stack Awards
To learn more about our privacy practices, please see our Privacy Policy.
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Sample interview questions
I would begin by mapping the workflow, decision points, data owners, exceptions, and required approvals with stakeholders. I would define narrowly scoped agents and deterministic tools for CRM and database actions, orchestrate them through a stateful workflow, and use authenticated APIs with audit logs. I would add human escalation for low-confidence or high-impact actions and monitor success, latency, cost, and error rates.
I would use structured outputs, schema validation, constrained tool access, deterministic business rules, retries, idempotency, and clear fallback paths. I would build an evaluation suite covering representative normal, edge-case, and adversarial inputs, then monitor production traces and user feedback. For critical actions, I would use confidence thresholds and human review.
I would ingest approved sources, clean and chunk documents based on their semantic structure, generate embeddings, and store them with metadata and access controls in a vector database. Retrieval would use hybrid search and reranking where appropriate, and prompts would require cited context rather than unsupported answers. I would evaluate retrieval relevance, answer faithfulness, freshness, and permission enforcement continuously.
I would establish a baseline for the current process, including completion time, error rate, rework, cost, and user satisfaction. I would define measurable targets, run staged pilots, and compare automated outcomes with human-reviewed ground truth. I would also track operational metrics such as tool failures, model cost, latency, escalation rate, and safety incidents.
I set clear design standards for prompts, tool interfaces, testing, security, and observability, then pair on early implementations and code reviews. I encourage small, measurable prototypes before production changes and explain the tradeoffs behind architectural decisions. I also help developers build evaluation habits so they can validate agent behavior rather than relying on anecdotal demonstrations.
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