Role Overview

Proofpoint is building the next generation of AI-powered security systems to protect organizations from rapidly evolving threats. We are looking for a highly skilled AI Engineer to help design and build production-grade agentic AI systems that power intelligent security workflows at scale. This role is focused on developing and deploying autonomous agents that are reliable, composable, cost-efficient, and capable of operating in real-world, high-throughput security environments. You will work closely with security researchers, platform engineers, and product teams to turn cutting-edge agentic AI techniques into robust, automated detection and response capabilities used in production. If you enjoy architecting multi-agent systems, optimizing for reliability and cost, orchestrating tool-using LLMs, and building observable pipelines - while solving difficult security problems - wed love to talk to you.

Job Title: AI Engineer (Agent Systems)

Location: Hyderabad; Athens; Sunnyvale

Key Responsibilities

- Design, build, evaluate, and deploy autonomous AI agents and multi-agent systems for security detection and response use cases
- Build reliable, cost-efficient agentic pipelines optimized for latency, accuracy, operational stability, and tool-use fidelity
- Develop orchestration frameworks for LLM-based agents with tool use, memory, planning, and multi-step reasoning
- Experiment with techniques such as ReAct, chain-of-thought prompting, structured output, retrieval-augmented generation (RAG), and agentic memory architectures; improve agent task completion quality while minimizing hallucination, failure modes, and unnecessary LLM calls
- Build scalable agent infrastructure and production-grade agentic workflow pipelines
- Partner with security researchers to transform detection and triage logic into agent-powered automated workflows




- Measure and optimize agent performance across task success rate, cost-per-run, latency, and reliability
- Contribute to evaluation frameworks, ground-truth datasets, and agent benchmarking workflows
- Monitor production agents and continuously improve robustness, observability, and failure recovery

Required Qualifications

- 2+ years of experience in AI Engineering, Applied AI, or ML Engineering
- Robust experience building and deploying agentic AI systems or LLM-powered applications in production
- Experience designing multi-step, tool-using agents using frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration
- Strong Python engineering skills
- Experience working with LLM APIs (OpenAI, Anthropic, Gemini) and open-source models via Hugging Face or similar
- Experience implementing RAG pipelines, vector stores, and semantic retrieval systems (e.g., FAISS, Weaviate, Pinecone, pgvector)
- Solid understanding of agent evaluation, prompt engineering, structured output parsing, and tool/function calling
- Experience deploying agentic systems in cloud or containerized environments
- Strong software engineering fundamentals and production mindset

Nice to Have

- Experience with security domains such as email security, threat intelligence, phishing detection, or SOC workflows
- Familiarity with fine-tuning or adapting LLMs for domain-specific agent behaviors
- Experience with observability tooling for LLM systems (e.g., LangSmith, Helicone, OpenTelemetry for AI)
- Knowledge of agent safety, guardrails, and human-in-the-loop design patterns
- Exposure to agentic memory systems (episodic, semantic, working memory) and long-horizon task planning

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Engineer (Bengaluru)
🏢 Proofpoint
📍 Bengaluru