We are looking for a forward-thinking and skilled Generative AI Engineer to join our [Engineering / AI Innovation] team. In this role, you will be at the forefront of building cutting-edge, LLM-powered applications, intelligent automation agents, and scalable retrieval systems. You will bridge the gap between advanced machine learning research and robust software engineering, transforming complex business challenges into production-grade generative AI products.
Key Responsibilities
- LLM Integration & Application Development: Design, build, and deploy production-grade applications integrating large language models (LLMs) via APIs from major providers (OpenAI, Anthropic, open-source models via Hugging Face/Ollama).
- RAG Architecture & Vector Engineering: Implement advanced Retrieval-Augmented Generation (RAG) pipelines, semantic search layers, and chunking strategies utilizing vector databases (e.g., Pinecone, Milvus, Qdrant, FAISS).
- Agentic Workflows: Develop multi-agent frameworks, automated reasoning loops, and autonomous workflows using tools like LangChain, LlamaIndex, or Semantic Kernel.
- Fine-Tuning & Model Evaluation: Fine-tune open-source foundational models (e.g., Llama, Mistral) for domain-specific tasks. Establish automated evaluation benchmarks, scoring frameworks (e.g., Ragas, TruLens), and guardrails for safety and hallucination reduction.
- MLOps & Production Deployment: Optimize inference performance, token latency, and cost. Deploy scalable, containerized AI solutions on cloud platforms (AWS/Azure/GCP) using Docker, Kubernetes, and serverless architectures.
- Cross-Functional Collaboration: Work closely with product managers, data scientists, and frontend/backend engineers to translate business requirements into technical AI roadmaps.
Key Skills & Qualifications
- Software Engineering Core: Strong proficiency in Python (minimum 3+ years) and standard software development practices (OOP, modular design, asynchronous programming, clean code, Git version control).
- Gen AI Ecosystem: Hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) and prompt engineering patterns.
- Data & Vector Systems: Solid understanding of data pipelines, embeddings, and working experience with vector databases.
- Web & API Frameworks: Experience building backend services and APIs using FastAPI or Flask.
- Cloud & Infrastructure: Familiarity with cloud-native development patterns, CI/CD pipelines, and deploying containerized applications on AWS, Azure, or GCP.
- Analytical Mindset: Strong problem-solving skills with a deep understanding of trade-offs between model size, cost, accuracy, and latency.
Preferred / Nice-to-Have Skills
- Experience with fine-tuning techniques (LoRA, QLoRA) and RLHF (Reinforcement Learning from Human Feedback).
- Background in evaluating LLM security vulnerabilities, prompt injection defenses, and enterprise data privacy compliance.
- Contributions to open-source AI projects or a strong portfolio of deployed generative AI apps.
- Degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.
What We Offer
- Competitive salary and performance bonus structure.
- Flexible working hours and hybrid/remote work culture.
- Continuous learning budget for certifications, conferences, and courses.
- Opportunity to work with cutting-edge AI technology that directly impacts our core products and users.
Pay: ₹50,000.00 - ₹90,000.00 per month
Work Location: In person
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