Agentic AI Lead (Exp 7-10 Years) Strategic
Overview
We’re hiring an Agentic AI Lead to architect, manage, and scale multi-agent systems that reason, plan, and act autonomously. You’ll lead a small team, ensure model efficiency, and orchestrate seamless production deployment through modern MLOps and LLMOps practices.
Responsibilities
- Key Responsibilities
- Lead the development of multi-agent workflows and architectures.
- Design model optimization and fine-tuning pipelines (parameter-efficient finetuning, LoRA, quantization).
- Oversee DevOps and MLOps pipelines — CI/CD, model versioning, containerization, and monitoring.
- Collaborate with data science teams on model evaluation and benchmarking.
- Drive production readiness — latency reduction, error recovery, and traceability.
- Mentor the Agentic AI developer team and review their code, design, and deployment.
Essential skills
- Core Skills
- Agent Frameworks: LangChain, OpenAI Agents SDK, or Google ADK.
- MLOps Stack: MLflow, Vertex AI, Airflow, Kubeflow, or Weights & Biases.
- LLMOps: Model finetuning, serving, optimization, and monitoring.
- DevOps: Kubernetes, Docker, Jenkins, Terraform, and CI/CD pipelines.
- Cloud Platforms: GCP (preferred), AWS, Azure.
- Vector Search: FAISS, Pinecone, Milvus, or Weaviate.
- Backend Integration: FastAPI, REST/gRPC, Pub/Sub, and event-driven design.
- Optimization Techniques: Finetuning (LoRA, QLoRA), model quantization, distillation, caching.
- System Design: Scalable APIs, message queues, observability, and fault tolerance.
- Programming: Python
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Desired skills
- Proven leadership in building production-grade AI systems.
- Experience deploying agents on Vertex AI, Databricks, or AWS Bedrock.
- Familiarity with RLHF, Agent safety evaluation, and governance frameworks.
