AI Engineer

We are looking for a highly skilled AI Engineer to design, build, and scale next-generation Agentic AI systems for enterprise security automation. This role is ideal for engineers who have hands-on experience building multi-agent systems, AI copilots, intelligent automation platforms, and enterprise-grade LLM applications.

You will work at the intersection of AI, cloud infrastructure, security automation, and distributed systems to create production-ready AI solutions that drive real-world outcomes.

Responsibilities:

• Design and build production-grade Agentic AI applications for enterprise security automation.
• Develop and deploy multi-agent systems, AI assistants, chatbots, and autonomous workflows.
• Build intelligent agents capable of tool usage, planning, reasoning, memory management, and workflow orchestration.
• Develop and optimize enterprise RAG (Retrieval-Augmented Generation) systems using vector databases and knowledge retrieval pipelines.
• Integrate external systems through Model Context Protocol (MCP) tools, APIs, and enterprise data sources.
• Work with modern LLM ecosystems, including Anthropic Claude, OpenAI, and cloud-hosted foundation models.
• Build scalable AI services leveraging AWS Bedrock and cloud-native architectures.
• Implement AI observability, governance, security, and safety guardrails.
• Collaborate closely with product, engineering, and security teams to deliver enterprise-grade AI capabilities.
• Evaluate emerging AI frameworks, agent architectures, and orchestration technologies.

Requirements:

• Experience building AI systems for cybersecurity use cases.
• Contributions to open-source AI projects.
• Experience evaluating and benchmarking LLMs and agent frameworks.
• Familiarity with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar agent orchestration frameworks.

Must-Have Skills and Experience:

• 8+ years of hands-on experience building GenAI applications in production.
• Strong programming expertise in Python, . NET (C#), and TypeScript.
• Hands-on experience building: Multi-agent systems, AI copilots, Chatbots, Tool-using agents, and AI-powered automation platforms.
• Deep understanding of LLM orchestration frameworks, Prompt engineering, Agent memory and planning architectures, Function/tool calling, and Structured outputs.
• Experience implementing: Enterprise RAG systems, Vector databases, Embeddings, Semantic search pipelines.
• Strong experience with AWS Bedrock (strongly preferred), AWS cloud services, and Containerized deployments.

Good to Have:

• Experience with Claude Agent SDK, OpenAI SDKs, or equivalent LLM provider frameworks.
• Experience integrating tools via Model Context Protocol (MCP).
• Knowledge of: AI security frameworks, LLM security, Prompt injection prevention, Data protection and governance, Responsible AI practices.
• Experience with: Docker, Kubernetes, MongoDB, OpenSearch/Elasticsearch.
• Exposure to: Cybersecurity, SOAR, SIEM, Security Operations.