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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Generative AI Researcher - **Company:** Tata Consultancy Services Limited - **Location:** Warren, MI, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Code Generation, Computer Programming, Python (Programming Language), Open Source Technology, Tensorflow, Reinforcement Learning, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Build Management, Information Technology, Virtual Agents - **Published:** August 9, 2026 - **Apply:** https://www.wayup.com/i-Information-Technology-and-Services-j-Generative-AI-Researcher-Tata-Consultancy-Services-923594124534253/ ## About the Role Education: Ph.D in Computer Science, Electrical Engineering, Mechanical Engineering or related streams. Technical Proficiency: Experience with generative AI (LLMs, diffusion models, generative architectures) Experience with agentic AI systems, reinforcement learning, or autonomous systems Strong programming skills in Python and experience with AI/ML frameworks (PyTorch, TensorFlow) Experience with LangChain, AutoGPT, Microsoft Autogen, or similar agent frameworks Proficiency with transformer architectures and fine-tuning techniques Deep understanding of prompt engineering, reasoning techniques, and LLM capabilities Experience with RAG systems, vector databases, and knowledge retrieval Knowledge of reinforcement learning, planning algorithms, and decision-making systems Familiarity with multi-agent systems and emergent behavior, Ph.D ## Description Job Summary: We are seeking a highly skilled and creative Entry Level - Generative AI Engineer to apply state-of-the-art generative models to solve complex challenges in automotive engineering. This role focuses on creating intelligent agents that leverage generative capabilities for reasoning, planning, and executing complex tasks autonomously. The ideal candidate will bridge the gap between generative AI's creative potential and agentic AI's autonomous action, developing systems that can understand, reason, and act in dynamic environments., Integrated AI System Development: Design and build AI agents that utilize large language models for reasoning and decision-making Develop systems where generative AI components enable sophisticated planning and problem-solving Create autonomous agents capable of using tools, APIs, and external systems through generative interfaces Implement multi-agent systems where generative AI facilitates communication and collaboration Generative AI Capabilities: Fine-tune and optimize large language models for specific agentic tasks Develop prompt engineering strategies for complex reasoning and chain-of-thought processes Implement RAG (Retrieval-Augmented Generation) systems to enhance agent knowledge and context Create generative models for code generation, content creation, and strategic planning within agent frameworks Agent Architecture & Autonomy: Build reflective agents that can critique and improve their own reasoning processes Design goal-oriented systems that use generative AI for planning and adaptation Implement memory architectures that allow agents to learn from experience and maintain context Develop safety mechanisms and oversight for autonomous generative agents Multi-Modal Agent Systems: Integrate vision, language, and action capabilities within agent frameworks Develop agents that can process and generate across multiple modalities (text, image, audio) Create embodied agents that interact with digital and physical environments Research & Innovation: Stay current with the latest academic research and open-source advancements in generative AI. Prototype new ideas and conduct experiments to validate their feasibility and impact. ## Related Videos - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Enter the Brave New World of GenAI with Vector Search](https://www.wearedevelopers.com/videos/844-enter-the-brave-new-world-of-genai-with-vector-search) - [The shadows that follow the AI generative models](https://www.wearedevelopers.com/videos/624-the-shadows-that-follow-the-ai-generative-models) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How to Use Generative AI to Accelerate Learning to Code](https://www.wearedevelopers.com/magazine/530-how-to-use-generative-ai-to-accelerate-learning-to-code) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)