AI Engineer with LLM
AI Engineer with LLM
Posted on :
26-08-2025
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1 Vacancy
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Job Description
Position Overview and nbsp;
We are seeking a highly skilled and forward-thinking and nbsp;AI Engineer specialized in Large Language Models (LLMs) and nbsp;to design develop and deploy innovative AI-powered applications and intelligent and nbsp;agents. The ideal candidate will possess deep expertise in and nbsp;LLM engineering including advanced prompt engineering strategies and nbsp;fine-tuning evaluation methodologies and the development of systems using frameworks like Lang chain/Lang Graph. You will have a strong background in software engineering and a passion for pushing the boundaries of whats possible with generative AI bringing solutions from and nbsp;ideation and research through to robust and scalable production deployment. and nbsp;
Experience: and nbsp;8 to 10 years of overall software development experience with and nbsp;at least 3 years specifically focused on AI development including significant hands-on experience with Large Language Models agent development and related technologies. and nbsp;Location: and nbsp;Bengaluru and nbsp;Employment Type: and nbsp;Full-time / Permanent and nbsp;
Key Responsibilities
- LLM Application and amp; Agent Development: and nbsp;Design build and optimize sophisticated applications intelligent and nbsp;AI agents and nbsp;and systems powered by Large Language Models.
- Advanced Prompt Engineering and amp; Optimization: and nbsp;Develop test iterate and refine advanced and nbsp;prompt engineering and nbsp;techniques to elicit desired behaviours ensure reliability and maximize performance from LLMs for various complex tasks.
- LLM Fine-Tuning and amp; Customization: and nbsp;Lead efforts in fine-tuning pre-trained LLMs on domain-specific datasets to enhance their capabilities and align them with specific business needs.
- LLM Evaluation and amp; Benchmarking: and nbsp;Establish and implement rigorous evaluation frameworks metrics and processes to assess LLM performance accuracy fairness safety and robustness. and nbsp;
- Framework Utilization (Langchain/LangGraph): and nbsp;Architect and develop complex LLM-driven workflows chains and nbsp;multi-agent systems and nbsp;and graphs using frameworks like Langchain and LangGraph. and nbsp;
- Cross-Functional Collaboration: and nbsp;Collaborate closely with Principal Architects (including those based internationally) data scientists software engineers and product teams to integrate LLM-based solutions into new and existing products and services. and nbsp;
- Performance Scalability and amp; Cost Optimization: and nbsp;Optimize LLM inference speed throughput scalability and cost-effectiveness for production environments. and nbsp;
- Stay Current with LLM Advancements: and nbsp;Continuously research evaluate and experiment with the latest LLM architectures open-source models and nbsp;prompt engineering methodologies agentic AI patterns and nbsp;fine-tuning methods and ethical AI considerations. and nbsp;
- LLMOps and amp; Governance: and nbsp;Contribute to building and maintaining LLMOps infrastructure including model versioning monitoring feedback loops data management for fine-tuning and governance for LLM deployments. and nbsp;
- API and amp; Service Development: and nbsp;Develop robust APIs and microservices to serve LLM-based applications and and nbsp;agents and nbsp;reliably and at scale. and nbsp;
- Documentation and amp; Knowledge Sharing: and nbsp;Create comprehensive technical documentation share expertise on LLM and and nbsp;agent development and nbsp;best practices and present findings to both technical and non-technical stakeholders. and nbsp;
Required Qualifications and nbsp;
- Educational Background: and nbsp;Bachelors or masters degree in computer science Artificial Intelligence Machine Learning Computational Linguistics or a closely related technical field. and nbsp;
- Professional Experience: and nbsp;5-7 years of progressive experience in software development with a minimum of and nbsp;3 years dedicated to AI development including substantial hands-on experience in designing building and deploying LLM-based systems and AI agents. and nbsp;
- Programming Proficiency: and nbsp;Expert proficiency in and nbsp;Python and nbsp;and its ecosystem relevant to AI and LLMs. and nbsp;
- LLM NLP and amp; Agent Expertise: and nbsp;Deep understanding of Natural Language Processing (NLP) concepts Transformer architectures the inner workings of Large Language Models and and nbsp;principles of AI agent design. and nbsp;
- LLM Frameworks and amp; Tools: and nbsp;Significant hands-on experience with LLM-specific libraries and frameworks such as and nbsp;Hugging Face Transformers Langchain LangGraph LlamaIndex and nbsp;and similar tools for building LLM applications and and nbsp;agents. and nbsp;
- Cloud Platform Experience: and nbsp;Solid experience with one or more major cloud platforms (AWS GCP Azure) and their respective AI/ML services particularly those for deploying and managing LLMs (e.g. Amazon Bedrock Google Vertex AI Azure OpenAI Service). and nbsp;
- Fine-Tuning and amp; Evaluation Experience: and nbsp;Demonstrable experience in fine-tuning LLMs and implementing robust evaluation strategies for both models and and nbsp;agent performance. and nbsp;
- MLOps/LLMOps Practices: and nbsp;Experience with MLOps principles and tools adapted for the LLM lifecycle (e.g. experiment tracking model registries CI/CD for LLMs and and nbsp;agent-based systems). and nbsp;
- Data Handling for LLMs: and nbsp;Understanding of data preprocessing augmentation and management techniques for training and fine-tuning LLMs. and nbsp;
- Version Control: and nbsp;Proficiency with Git and collaborative development workflows. and nbsp;
Preferred Qualifications and nbsp;
- Advanced LLM Architectures and amp; Prompt Engineering: and nbsp;Deep experience with various LLM architectures their trade-offs and mastery of advanced and nbsp;prompt engineering techniques. and nbsp;
- Autonomous Agent and amp; Multi-Agent Systems: and nbsp;Proven experience in designing developing and deploying autonomous and nbsp;AI agents and nbsp;or complex multi-agent systems. and nbsp;
- Vector Databases: and nbsp;Familiarity with vector databases (e.g. Pinecone Weaviate Milvus Chroma) for retrieval augmented generation (RAG) and semantic search in and nbsp;agentic architectures. and nbsp;
- Distributed Systems for LLMs: and nbsp;Knowledge of distributed training and inference techniques for very large models. and nbsp;
- Ethical AI and amp; Responsible LLM/Agent Development: and nbsp;Strong understanding of ethical considerations bias detection and responsible AI practices in the context of LLMs and and nbsp;AI agents. and nbsp;
- Research and amp; Publications: and nbsp;Contributions to LLM or and nbsp;AI agent and nbsp;research publications in relevant conferences/journals or active participation in open-source LLM/agent projects. and nbsp;
- Domain-Specific LLM/Agent Applications: and nbsp;Experience applying LLMs and and nbsp;agents and nbsp;to solve problems in specific industry domains. and nbsp;
- Cloud Certifications: and nbsp;Relevant cloud certifications (e.g. AWS Certified Machine Learning Google Professional Machine Learning Engineer and nbsp;Microsoft Certified: Azure AI Engineer Associate or similar MCP credentials). and nbsp;
Technical Skillset Summary and nbsp;
- Programming: and nbsp;Python (expert) SQL. and nbsp;
- LLM/NLP/Agent Frameworks: and nbsp;Hugging Face Transformers and nbsp;Langchain LangGraph LlamaIndex and nbsp;PyTorch TensorFlow and nbsp;frameworks for agent development. and nbsp;
- Cloud Platforms and amp; LLM Services: and nbsp;AWS (SageMaker Bedrock) GCP (Vertex AI) Azure (Machine Learning Azure OpenAI Service). and nbsp;
- Tools: and nbsp;Docker Kubernetes MLflow Weights and amp; Biases and nbsp;Vector Databases (e.g. Pinecone Weaviate). and nbsp;
- Databases: and nbsp;Relational (SQL Server PostgreSQL MySQL) NoSQL (MongoDB) and Vector Databases. and nbsp;
Soft Skills and nbsp;
- Exceptional analytical creative and critical thinking skills with a talent for innovative problem-solving in the generative AI and and nbsp;intelligent agent and nbsp;space. and nbsp;
- Outstanding communication skills with the ability to explain complex LLM concepts and and nbsp;agent system designs and nbsp;to diverse audiences. and nbsp;
- Proven ability to work effectively both independently and as a key contributor in collaborative agile teams. and nbsp;
- Meticulous attention to detail especially regarding data quality model behavior and nbsp;agent reliability and nbsp;and system robustness. and nbsp;
- A proactive highly adaptable mindset with an insatiable curiosity and passion for the rapidly evolving field of Large Language Models and and nbsp;AI agents. and nbsp;
Employment Type
Full Time
Key Skills
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