Applied AI Engineer
VOLTO Consulting
Hyderabad, Telangana, India
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.