AI Agent Engineer

Job Description

Location: Remote - US
Engagement Type: Contract
Tech assessment - YES (Paid - $500 USD)
Rate: $150–$250/hour (depending on experience)
Start Date: Immediate
Team: Collaborating with CTD’s Belgrade-based engineering and data science team
Next Step in the Process: Candidates selected to move forward will be invited to complete a 72-hour paid test project. This test is designed to be realistic and scoped for success—giving both sides a chance to evaluate fit before proceeding further.

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About the Role

We’re seeking an experienced Fractional AI Consultant to help us design, prototype, and deploy intelligent agents tailored to real-world business applications. This is a hands-on, technical role focused on building systems that combine retrieval, reasoning, memory, and safe execution in production.

You’ll be working alongside our in-house engineering and data science team to bring an agent from concept to deployment—quickly and pragmatically.

This is a remote contract engagement with competitive hourly compensation.

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What You’ll Do

• Architect and build intelligent agents from scratch, with thoughtful decisions around using existing tools vs. custom solutions.
• Implement and prioritize key components such as memory systems, reasoning frameworks, and vector-based retrieval.
• Fine-tune or integrate LLMs for specific use cases, balancing power with privacy and reliability.
• Design data pipelines for ingesting, transforming, and syncing content from various sources (relational DBs, document stores, APIs).
• Build safe execution layers for agents interfacing with APIs and external systems.
• Develop prompt strategies and memory architectures that generalize across varied user intents.
• Monitor and evaluate agent performance using appropriate metrics (latency, hallucination, accuracy, etc.).
• Collaborate closely with internal teams to iterate rapidly and ship working prototypes.

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What We’re Looking For

We will evaluate candidates based on their ability to:

• Rapidly build functional prototypes and iterate.
• Combine deterministic querying with semantic/vector search.
• Integrate LLMs intelligently—not as a catch-all solution.
• Communicate clearly in both code and documentation.
• Make pragmatic, thoughtful decisions around architecture, trade-offs, and timelines.
• Work collaboratively and adapt to changing needs.
• Start immediately.

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Bonus Points

• Experience advising organizations on broader AI adoption strategies.
• Prior experience integrating AI agents with external systems (e.g., APIs, tools, databases) safely and effectively.

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How to Apply

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