Agent Trust Core
Sr. Agentic AI Engineer
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Agentic AI Engineer
Agent Trust Core develops intelligent AI agents that safeguard enterprise AI enablement solutions. The company offers a comprehensive suite of security-focused agents that work together to protect AI systems across industries and use cases. A team of specialized AI engineers designs and builds secure, production-ready agents tailored to each client’s workflows and regulatory environment. From initial concept through deployment, Agent Trust Core focuses on secure, reliable AI implementations that help organizations innovate with confidence.
Role Description
The Agentic AI Engineer role is a full-time hybrid position based in the London Area. This role focuses on designing, implementing, and maintaining agentic AI systems that secure and enhance clients’ AI enablement solutions.
The engineer will collaborate with product, security, and client teams to translate business requirements into robust AI workflows, conduct performance and safety evaluations, and iterate on models and agents based on monitoring and feedback. The position also involves documenting architectures, contributing to internal best practices for secure AI deployment, and staying current with developments in agentic AI, NLP, and AI safety.
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Required Skills
- 8 to 12 years in Software development with Python, Agentic AI, and LLMs.
- Proficient in Python and Hugging Face Transformers, Hugging Chat Assistant.
- Fine-tune foundational models (e.g., Hugging Face, OpenAI) to deliver use cases.
- Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments.
- Build using transformers.js and huggingface.js for AI and Machine learning.
- Collaborate with front-end engineers to design and implement APIs that effectively serve front-end needs.
- Full-stack using (React, Node.js) and API development.
Responsibilities
- AI Development: Design, train, fine-tune, and deploy LLMs with reasoning capabilities.
- Retrieval-Augmented Generation (RAG): Implement, optimize, and scale RAG pipelines for effective information retrieval from structured and unstructured sources.
- Multi-Agent Systems: Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy.
- AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services.
- End-to-End AI Product Development: Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring.
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Qualifications
- Strong foundation in Computer Science, including algorithms, data structures, and distributed systems.
- Practical experience with Software Development for production environments, using modern programming languages and development tools.
- Expertise in Neural Networks and Pattern Recognition, including training, evaluation, and optimization of machine learning models.
- Hands-on experience with Natural Language Processing (NLP) techniques and frameworks for building conversational or task-oriented AI agents.
- Knowledge of AI safety, security best practices, and risk mitigation for deployed AI systems.
- Experience with cloud platforms and MLOps tooling (e.g., CI/CD, model monitoring, version control) is beneficial.
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