Senior AI Engineer

Zoho; Hyderabad; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

NopalCyber Hyderabad is seeking a Senior AI Engineer to lead the design, development, and productionization of Generative AI, Agentic AI, and AI-driven automation for enterprise cybersecurity products.

The role requires hands-on implementation, end-to-end ownership, and strong Python/FastAPI capabilities, with experience in LangChain, RAG, and secure AI practices. Remote-ready options may vary by project.

Qualifications

• Hands-on GenAI and agentic AI development experience.
• Strong production-grade AI systems experience.
• Experience with enterprise cybersecurity integration is a plus.

Responsibilities

• Own AI/GenAI initiatives end-to-end from problem to deployment.
• Design Agentic AI and multi-agent systems for autonomous ops.
• Architect and develop LLM-powered apps, RAG pipelines, and memory.
• Implement agent orchestration, tool calling, and guardrails.
• Build enterprise-grade RAG solutions with vector search and embeddings.
• Integrate AI agents with enterprise systems via REST/Webhooks.
• Ensure evaluation: accuracy, latency, cost, and reliability.
• Mentor engineers and contribute to AI standards and practices.

Skills

GenAI

Agentic AI

Python FastAPI

LangChain

RAG

LLM production

Vector DBs

REST APIs

CI/CD

Security basics

Education

B.Tech/B.E./M.Tech in CS/AI

Tools

Docker

AWS

MySQL/PostgreSQL

OpenAI/Azure OpenAI

ML frameworks

Job description

NopalCyber makes cybersecurity manageable, affordable, reliable, and powerful for companies that need to be resilient and compliant. Managed extended detection and response (MXDR), attack surface management (ASM), breach and attack simulation (BAS), and advisory services fortify your cybersecurity across both offense and defense. AI-driven intelligence in our Nopal360° platform, our NopalGo mobile app, and our proprietary Cyber Intelligence Quotient (CIQ) lets anyone quantify, track, and visualize their cybersecurity posture in real-time. Our service packages, which are each tailored to a client’s needs and budget, and external threat analysis, which provides critical intelligence at no-cost, help to democratize cybersecurity by making enterprise-grade defenses and security operations available to organizations of all sizes. NopalCyber lowers the barrier to entry while raising the bar for security and service.

Job Description

Job Description – Senior AI Engineer (GenAI & Agentic AI)

Location: Hyderabad Experience: 5+ Years Total | 2+ Years Hands-on GenAI & Agentic AI Employment Type: Full-time

About the Role

We are looking for a Senior AI Engineer to drive the design, architecture, development, and productionization of Generative AI, Agentic AI, and AI-driven automation solutions for enterprise cybersecurity products.

The ideal candidate should be able to independently own AI initiatives end-to-end—from understanding the business problem and defining the AI approach to architecture, implementation, integration, evaluation, deployment, monitoring, and continuous improvement. The role requires strong hands-on engineering capability rather than research-only or API-integration experience.

Key Responsibilities

• Own AI/GenAI initiatives end-to-end, translating business and cybersecurity requirements into scalable AI solutions.
• Design and implement Agentic AI and Multi-Agent systems for autonomous investigation, decision support, workflow automation, threat analysis, and security operations.
• Architect and develop LLM-powered applications, RAG pipelines, AI agents, conversational systems, and intelligent automation workflows.
• Design agent orchestration including planning, tool/function calling, memory, state management, task decomposition, retries, human-in-the-loop, and guardrails.
• Build enterprise-grade RAG solutions, including document ingestion, preprocessing, chunking, embeddings, vector search, metadata filtering, reranking, and contextual response generation.
• Integrate AI agents with enterprise and cybersecurity systems through REST APIs, webhooks, SDKs, databases, SIEM/EDR/security tools, & third‑party services.
• Establish AI evaluation mechanisms covering accuracy, relevance, groundedness, hallucination, tool‑call accuracy, latency, reliability, & cost.
• Optimize LLM applications for performance, scalability, reliability, token consumption, latency, and inference cost.
• Design secure AI solutions addressing prompt injection, data leakage, access control, sensitive information handling, unsafe tool execution, and AI-specific security risks.
• Develop production‑ready AI services and APIs using Python/FastAPI, with appropriate logging, error handling, testing, observability, and monitoring.
• Independently troubleshoot complex issues across LLM, RAG, agent orchestration, integrations, APIs, databases, and deployment environments.
• Mentor AI engineers and contribute to AI architecture standards, reusable frameworks, engineering best practices, and technical decision‑making.

Must‑Have Skills & Experience

• AI / GenAI / Agentic AI
• 5+ years total software/engineering experience, with at least 2+ years hands‑on experience in GenAI and Agentic AI.
• Strong practical experience building LLM‑based production applications and AI agents.
• Strong understanding of Agentic AI, Multi‑Agent Systems, AI workflows, tool calling/function calling, planning, memory, state management, human‑in‑the‑loop patterns and fine‑tuning.
• Hands‑on experience with LangChain and/or LangGraph; experience with CrewAI, AutoGen, Agno, LlamaIndex or similar frameworks is a plus.
• Strong expertise in RAG architecture, embeddings, vector search, hybrid search, reranking, and knowledge‑base design.
• Hands‑on experience with vector databases such as Qdrant, Milvus, Pinecone, Weaviate, Chroma or OpenSearch.
• Strong prompt engineering skills, including structured outputs, few‑shot prompting, prompt optimization, and context engineering.
• Experience with LLM evaluation, hallucination reduction, guardrails, AI observability, and production monitoring.
• Experience with LLM providers/models such as OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Llama, Mistral or equivalent.
• Strong Python programming skills with FastAPI, Pydantic, async programming, REST APIs, and API integration.
• Working knowledge of SQL/NoSQL databases, preferably MySQL/PostgreSQL
• Experience with Docker and cloud‑based AI deployment, preferably AWS.
• Strong understanding of Git, CI/CD, testing, debugging, logging, and production support.

Cybersecurity – Preferred

• Experience building AI solutions for SOC, SIEM, EDR/XDR, vulnerability management, threat intelligence, incident response, or attack surface management.
• Understanding of CVE/CVSS, MITRE ATT&CK, threat intelligence, security alerts, vulnerabilities, and security operations workflows is highly desirable.

Good to Have

• Working knowledge of AWS services such as ECS/EKS, Lambda, S3, Bedrock, RDS, OpenSearch, and CloudWatch.
• Experience with MCP (Model Context Protocol) and modern agent/tool integration patterns.
• Exposure to LoRA/PEFT, open‑source LLMs, model serving, or inference optimization.

Requirements

What We Expect

The successful candidate should be able to take an AI initiative from “business problem → AI approach → architecture → POC → production implementation → evaluation → deployment → monitoring” with minimal supervision.

We are specifically looking for an engineer who can make architecture decisions, write production‑quality code, integrate enterprise systems, troubleshoot independently, and continuously improve AI solutions—not someone limited to prompt writing or calling LLM APIs.

Education: B.Tech/B.E./M.Tech in Computer Science, AI/ML, Data Science, or related discipline.