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Staff Engineer - AI Engineering

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Onsite

Staff Engineer - AI Engineering

GE VERNOVA

Staff Engineer - AI Engineering

Skills

Google Cloud PlatformDeep LearningDockerNodeTypescriptPythonGolangJavaPyTorchTensorFlowMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingJavascript

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

22 September 2026

What they need


Job Description SummaryGE Vernova is seeking a highly skilled AI Engineer to design, develop, and deploy advanced autonomous AI agents leveraging LLMs and advanced AI/ML techniques. The ideal candidate will build intelligent Agents capable of perceiving, reasoning, and acting within complex digital or real-world environments, integrating AI models into scalable applications that solve real-world business challenges autonomously.

Responsible for departmental operations planning/execution or is focused on execution of professional activities within a technical discipline. Functions with some autonomy but guided by established policies or review of end results.
The job allows modification of procedures and practices covering work as long as the end results meet standards of acceptability (quality, volume, timeliness etc.).Job Description

Key Responsibilities:

  • Design, implement, and optimize AI Agents using LLMs, reinforcement learning, planning algorithms, and decision-making frameworks.
  • Develop scalable multi AI Agent architectures supporting long horizon reasoning, autonomy, planning, interaction, and complex task completion.
  • Integrate AI Agents with APIs, backend services, databases, and enterprise applications.
  • Prototype, deploy, and maintain AI-driven systems ensuring reliability and performance in production environments.
  • Optimize agent behavior through continuous feedback, reinforcement learning, and user interaction.
  • Collaborate closely with research, engineering, product, and deployment teams to iterate on agent capabilities and innovate continuously.
  • Monitor AI Agent performance, conduct rigorous evaluations, implement safety guardrails, and ensure ethical AI practices.
  • Document AI Agent architectures, design decisions, workflows, and maintain comprehensive technical documentation.
  • Stay current with emerging AI technologies, contribute to platform and tooling improvements, and share knowledge within the team.
  • Your mission is to push the boundaries of planning, reasoning, and agentic intelligence. You will design and implement large-scale AI/ML solutions integrating the latest state of the art research in our global products

Core Technical Skills:

  • Proficiency in Python and/or languages like JavaScript, TypeScript, Node.js, or Java, Go, with strong coding and software engineering practices.
  • Expertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, commercial or open source LLMs.
  • Hands-on experience with LLMs, prompt engineering, and natural language processing (NLP).
  • Knowledge of agent orchestration platforms and multi-agent systems (e.g., AutogenAI, LangGraph, MCP protocol).
  • Familiarity with data management, vector databases, semantic retrieval, and real-time data pipelines.
  • Experience deploying AI systems on cloud platforms (AWS, Google Cloud) with container orchestration (Docker, Kubernetes).
  • Strong understanding of machine learning model training, fine-tuning, and evaluation techniques.
  • Awareness of AI ethics, data privacy, and secure handling of sensitive information.

Qualifications:

  • Masters/ PhD degree in Computer Science, AI/ML,Engineering, Mathematics, or related field with 5+ years of relevant experience.
  • Minimum 3 years of experience in AI, GenAI application development deployment particularly with autonomous agent systems or related AI software engineering roles.
  • Demonstrated ability to work independently in fast-paced, experimental environments.
  • Hands-on experience designing and building GenAI apps that allow users to experience AI use cases supporting features like agent orchestration, multi-step reasoning, prompt engineering, RAG integration, and model selection
  • Expertise with LLMs and deep learning models, machine learning lifecycle management, data generation methods, model training validation coupled with strong fundamentals and passion in software engineering and system architecture

Additional Information

Relocation Assistance Provided: Yes

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