Note : If screened-in, you will be invited for initial rounds on 28th November 2026 (Saturday) in Hyderabad.JOB SUMMARY :Lead : 7+ years in software/ML engineering, with 3+ years leading development and production deployments of complex distributed or AI systems.The Lead AI Engineer carries two connected mandates: building the agentic AI platform and deploying it into client environments. You will work alongside the Technical Architect and EM to translate architecture into working code and verified deployments.KEY RESPONSIBILITIES :1. Agentic AI Platform Bring Up :- Multi-agent runtime deployment: Configure tool-call allowlists, agent registry, and validate agent topology.- LLM inference and gateway configuration: Size GPU node pools, configure LiteLLM gateway, and manage rate limits.- RAG and vector store bring-up: Stand up vector stores, manage per-tenant collections, and validate embedding pipelines.- Workflow orchestration bring-up: Configure graph databases and workflow orchestrators.2. Technical Expertise:- Event-driven architecture: Kafka topology and Flink stateful stream processing.- Graph database architecture: Neo4j causal cluster topology and Cypher performance optimization.- Distributed workflow orchestration: LangGraph StateGraph design and dynamic DAG injection.- Kubernetes platform architecture:



Cluster topology for heterogeneous workloads and service mesh configuration.- Cloud-agnostic IaC architecture: Terraform module hierarchy and zero-drift enforcement.- Observability architecture: Prometheus metric design and Grafana dashboard governance.3. Client-Facing Technical Leadership :- Client stakeholder management: Act as the technical face of the deployment to client IT and security teams.- Deployment runbook authorship: Maintain environment-specific runbooks for client operations.- Knowledge transfer and enablement: Train client engineers for day-2 operations.- Cross-team coordination: Sequence deployments across internal and client teams.PREFERRED QUALIFICATIONS :- 7+ years of skilled experience in software or ML engineering, with at least 3 years leading deployment of complex distributed or AI systems.- Direct experience deploying Kubernetes-based platforms into enterprise settings.- Hands-on familiarity with agentic AI stacks (graph databases, vector stores, event streaming, GPU-served inference).- Bachelor's or Master's degree in Computer Science or related technical discipline.- Relevant certifications (CKA, CKAD, AWS/GCP Architect) are a plus. (ref:hirist.tech)

📌 Qentelli - Lead AI Engineer - Machine Learning/RAG/LLM (Hyderabad)
🏢 Hirist.tech
📍 Hyderabad