Principal Engineer – AI Specialist

F5 F5 · Enterprise · Hyderabad, India

Principal Engineer specializing in AI systems, focusing on designing, deploying, and optimizing advanced AI solutions including GPT-based systems, reinforcement learning, and autonomous agents. The role involves developing intelligent agents, enabling generative AI capabilities, and integrating state-of-the-art AI techniques. It also requires building and optimizing large-scale distributed AI infrastructure, implementing observability systems, and creating frameworks for data ingestion and automated AI workflows. Leadership and mentorship are key components, along with strategic roadmap creation and collaboration with product and engineering teams.

What you'd actually do

  1. Lead the design and deployment of advanced AI-driven systems and models, including GPT-based solutions (GPT-4.x, OpenAI APIs), reinforcement learning frameworks, and autonomous agentic workflows.
  2. Develop intelligent agents capable of handling complex tasks, decision-making, and automating workflows within F5 products and platforms.
  3. Develop and optimize large-scale distributed AI infrastructure, ensuring fault tolerance, resilience, scalability, and performance in global workloads.
  4. Implement advanced observability systems for AI applications, leveraging telemetry pipelines (e.g., OpenTelemetry, Prometheus) and ensuring data quality validation.
  5. Create best-in-class AI architecture roadmaps, ensuring alignment with organizational goals and the latest advancements in AI technology.

Skills

Required

  • Python
  • Go
  • JavaScript
  • Kubernetes
  • OpenShift
  • Terraform
  • Helm
  • Kafka
  • Flink
  • Spark
  • OpenTelemetry
  • Prometheus
  • Grafana
  • Datadog
  • LangChain
  • Hugging Face Transformers
  • GPT-4.x
  • transformer models
  • reinforcement learning
  • NLP
  • computer vision
  • predictive analytics
  • decision systems
  • multi-agent frameworks
  • GANs
  • sequence modeling
  • unsupervised learning
  • multi-modal AI systems
  • RASA conversational systems
  • distributed systems architecture
  • MLOps
  • fault tolerance
  • latency optimization
  • anomaly detection
  • telemetry validation
  • benchmarking tools
  • AI APIs
  • AI algorithms

Nice to have

  • AWS Certified Machine Learning
  • Microsoft Azure AI Engineer
  • Google Professional Machine Learning Engineer
  • TensorFlow Extended
  • DeepMind R&D frameworks

What the JD emphasized

  • 10+ years of hands-on experience in AI research, development, and deployment
  • Expertise in building multi-modal AI systems capable of handling text, images, audio, and structured data.

Other signals

  • deployment of advanced AI-driven systems
  • Develop intelligent agents
  • Enable generative AI capabilities
  • Develop and optimize large-scale distributed AI infrastructure
  • Implement advanced observability systems for AI applications