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
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Lead the development of multi-agent workflows and architectures.
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Design model optimization and fine-tuning pipelines (parameter-efficient finetuning, LoRA, quantization).
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Oversee DevOps and MLOps pipelines — CI/CD, model versioning, containerization, and monitoring.
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Collaborate with data science teams on model evaluation and benchmarking.
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Drive production readiness — latency reduction, error recovery, and traceability.
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Mentor the Agentic AI developer team and review their code, design, and deployment.
Qualifications:
BTech, BE, MCA
Essential skills:
Core Skills
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Agent Frameworks: LangChain, OpenAI Agents SDK, or Google ADK.
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MLOps Stack: MLflow, Vertex AI, Airflow, Kubeflow, or Weights & Biases.
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LLMOps: Model finetuning, serving, optimization, and monitoring.
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DevOps: Kubernetes, Docker, Jenkins, Terraform, and CI/CD pipelines.
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Cloud Platforms: GCP (preferred), AWS, Azure.
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Vector Search: FAISS, Pinecone, Milvus, or Weaviate.
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Backend Integration: FastAPI, REST/gRPC, Pub/Sub, and event-driven design.
Desired skills:
- Proven leadership in building production-grade AI systems.
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Experience deploying agents on Vertex AI, Databricks, or AWS Bedrock.
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Familiarity with RLHF, Agent safety evaluation, and governance frameworks.
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Experience:
7–10 Years Experience
