Leading Agentic AI Solutions Architect

10 hours ago

Vijayawada, Andhra Pradesh, India beBeeArtificial Full time ₹ 20,00,000 - ₹ 30,00,000

Job Title:

  • Senior AI Engineer

Job Overview:

We are seeking a skilled Senior AI Engineer to architect and implement large-scale agentic AI solutions. The ideal candidate will have extensive experience in designing, deploying, and maintaining multi-agent AI systems for log analysis, anomaly detection, and incident response.

Key Responsibilities:

  • Operationalize large language models and agentic workflows to automate security decision-making and threat response.
  • Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response.
  • Build proof-of-concept GenAI solutions and evolve them into production-ready components using reusable best practices.
  • Implement CI/CD pipelines for model training, validation, and deployment with GitHub Actions and AWS CodePipeline.
  • Manage model versioning with MLflow and DVC, set up automated testing, rollback procedures, and retraining workflows.
  • Automate cloud infrastructure provisioning with Terraform and develop REST APIs and microservices containerized with Docker and Kubernetes.
  • Monitor models and infrastructure through CloudWatch, Prometheus, and Grafana; analyze performance and optimize for cost and SLA compliance.
  • Collaborate with data scientists, application developers, and security analysts to integrate agentic AI into existing security workflows.

Qualifications:

  • Bachelor's or Master's in Computer Science, Data Science, AI, or related quantitative discipline.
  • 4+ years of software development experience, including 3+ years building and deploying LLM-based/agentic AI architectures.
  • In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG).
  • Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI, or equivalent agentic frameworks.
  • Strong proficiency in Python and production-grade coding for data pipelines and AI workflows.
  • Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices.
  • Extensive AWS experience with Bedrock, SageMaker, Lambda, EKS/ECS, S3 (Athena, Glue, Snowflake preferred).
  • Infrastructure as Code skills with Terraform.
  • Experience building REST APIs, microservices, and containerization with Docker and Kubernetes.
  • Solid data science fundamentals: feature engineering, model evaluation, data ingestion.
  • Understanding of cybersecurity principles, SIEM data, and incident response.
  • Excellent communication skills for both technical and non-technical audiences.

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