Proofpoint
AI Engineer (Agent Systems)
ClosedThis opening has closed. New ones like it are posted on WhatsApp every day.
Get new jobs on WhatsApp- Location
- Hyderabad
- Work mode
- See listing
- Experience
- 2+ yrs exp
- Pay
- ₹16–28 LPA (Est.)
- Type
- Full-time job, AI & ML
- Added
- 11 November 2026
- Apply by
- 12 November 2026
About this role
Proofpoint is a cybersecurity company that protects people, data and AI agents across email, cloud and collaboration tools. This AI Engineer role in Hyderabad sits on a team building agentic AI systems that automate security detection and response. Day to day, you would design, test and deploy LLM-based agents that use tools, memory and multi-step reasoning, and tune them for reliability, latency and cost. You would work with security researchers, platform engineers and product teams to turn triage and detection logic into automated workflows, and you would monitor those agents in production. The role asks for at least 2 years of AI or ML engineering experience, so it suits engineers who have already shipped LLM applications rather than fresh graduates.
Proofpoint was hiring for AI Engineer (Agent Systems), a full-time role based in Hyderabad.
Who can apply: 2+ yrs exp. Skills: Python, LLM agents, RAG, LangGraph / AutoGen, Vector databases.
This opening has closed (closed on 2026-11-12). Open roles like it are listed on this page and at hirastra.com/jobs.
What you'll do
- Design, build, evaluate and deploy autonomous AI agents and multi-agent systems for security detection and response
- Develop orchestration for LLM agents with tool use, memory, planning and multi-step reasoning
- Work with security researchers to convert detection and triage logic into agent-powered workflows
- Measure and optimise agents for task success, cost per run, latency and reliability
- Contribute to evaluation frameworks, ground-truth datasets and agent benchmarking
- Monitor production agents and improve robustness, observability and failure recovery
What you need
- 2+ years in AI engineering, applied AI or ML engineering
- Experience building and deploying agentic AI or LLM-powered applications in production, using frameworks such as LangGraph, AutoGen or CrewAI
- Strong Python skills and experience with LLM APIs (OpenAI, Anthropic, Gemini) and open-source models
- Experience with RAG pipelines and vector stores such as FAISS, Weaviate, Pinecone or pgvector
- Understanding of agent evaluation, prompt engineering, structured output and tool/function calling
- Experience deploying systems in cloud or containerised environments
Skills
- Python
- LLM agents
- RAG
- LangGraph / AutoGen
- Vector databases
"Est." = Hirastra's estimate based on market data, not an official figure.
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