Lead AI Developer
Skills
About the role
Overview:
Lead AI Developer 7 to 10 experience
Responsibilities:
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
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.
Qualifications:
BTech, BE, MCA
Desired skills:
Strong understanding of AI safety, governance, and trust frameworks.
Experience implementing MCP, multi-agent orchestration, or custom reasoning layers.
Proven success in leading enterprise-scale AI transformation initiatives.
Experience:
7–10 Years Experience
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