Applied AI Engineer

Lead / Senior Applied AI Engineer

Experience: 5–15 Years

Employment Type: Full-Time

Location: Hyderabad (only local Candidates)

Job Description

We are looking for a Lead / Senior Applied AI Engineer with strong hands-on experience in Generative AI, Agentic AI, LLM orchestration, and enterprise AI solutions . The ideal candidate should have experience designing and deploying production-grade AI applications using Python, LangGraph, Agentic RAG, Multi-Agent Systems, and modern LLM technologies.

Key Responsibilities

• Design and develop Agentic AI and Multi-Agent Systems using Python and LangGraph .
• Build scalable Agentic RAG pipelines and enterprise-grade LLM applications.
• Implement LLM orchestration , tool calling, workflow automation, and intelligent agents.
• Work with MCP (Model Context Protocol) to integrate AI agents with enterprise tools, data sources, and services.
• Develop effective prompt engineering strategies, including structured prompting and reusable prompt frameworks.
• Implement Prompt Injection Defense , hallucination mitigation, grounding, validation, and AI safety mechanisms.
• Design and implement structured outputs using schemas and validation frameworks.
• Work with leading LLM platforms/models including Claude and other enterprise LLMs.
• Ensure AI solutions follow AI Safety, security, privacy, and responsible AI principles.
• Build CI/CD pipelines and production deployment workflows using Docker, Kubernetes, and DevSecOps practices.
• Develop and deploy AI workloads on GCP and integrate with enterprise cloud services.
• Collaborate with engineering, security, data, and business teams to deliver enterprise AI solutions.
• Ensure AI applications align with applicable regulatory and governance requirements, including EU AI Act and DORA .
• Lead technical discussions, architecture decisions, code reviews, and mentoring of AI engineering teams.

Required Technical Skills

• Python
• LangGraph
• Agentic RAG
• Multi-Agent Systems
• LLM Orchestration
• MCP (Model Context Protocol)
• Prompt Engineering
• Prompt Injection Defense
• Hallucination Mitigation
• Structured Outputs
• Claude / LLMs
• Generative AI / Agentic AI
• AI Safety & Responsible AI
• CI/CD
• Docker
• Kubernetes
• DevSecOps
• GCP / Google Cloud
• Enterprise AI architecture and deployment

AI Governance & Compliance

• Understanding of EU AI Act requirements and AI risk management.
• Knowledge of DORA (Digital Operational Resilience Act) and its relevance to technology/AI systems.
• Experience implementing AI security, governance, auditability, monitoring, and compliance controls.

Preferred Skills

• Experience building production-grade enterprise AI platforms .
• Knowledge of LLM evaluation, observability, guardrails, and AI monitoring.
• Experience with API development and microservices.
• Strong understanding of cloud-native architecture and secure software development.
• Experience leading AI engineering teams and working with enterprise stakeholders.