At Codvo software and people transformations go hand-in-hand We are a global empathy-led technology services company where product innovation and mature software engineering are embedded in our core DNA Our core values of Respect Fairness Growth Agility and Inclusiveness guide everything we do We continually expand our expertise in digital strategy design architecture and product management to offer measurable results and outside-the-box thinking About the Role We are seeking a highly skilled and experienced Senior AI Engineer to lead the design development and implementation of robust and scalable pipelines and backend systems for our Generative AI applications In this role you will be responsible for orchestrating the flow of data integrating AI services developing RAG pipelines working with LLMs and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions You will also be expected to apply modern LLMOps practices handle schema-constrained generation optimize cost and latency trade-offs mitigate hallucinations and ensure robust safety personalization and observability across GenAI systems Responsibilities Generative AI Pipeline Development Design and implement scalable and modular pipelines for data ingestion transformation and orchestration across GenAI workloads Manage data and model flow across LLMs embedding services vector stores SQL sources and APIs Build CI CD pipelines with integrated prompt regression testing and version control Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows Monitor system performance using tools like Langfuse or Prometheus Data and Document Ingestion Develop systems to ingest unstructured PDF OCR and structured SQL APIs data Apply preprocessing pipelines for text images and code Ensure data integrity format consistency and security across sources AI Service Integration Integrate external and internal LLM APIs OpenAI Claude Mistral Qwen etc Build internal APIs for smooth backend-AI communication Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy Retrieval-Augmented Generation RAG Pipelines Build hybrid RAG pipelines using vector similarity FAISS Qdrant and structured data SQL API Design custom retrieval strategies for multi-modal or multi-source documents Apply post-retrieval ranking using DPO or feedback-based techniques Improve contextual relevance through re-ranking chunk merging and scoring logic LLM Integration and Optimization Manage prompt engineering model interaction and tuning workflows Implement LLMOps best practices prompt versioning output validation caching KV store and fallback design Optimize generation using temperature tuning token limits and speculative decoding Integrate observability and cost-monitoring into LLM workflows Backend Services Ownership Design and maintain scalable backend services supporting GenAI applications Implement monitoring logging and performance tracing Build RBAC Role-Based Access Control and multi-tenant personalization Support containerization Docker Kubernetes and autoscaling infrastructure for production Required Skills and Qualifications Education Bachelor s or Master s in Computer Science Artificial Intelligence Machine Learning or related field Experience 5 years of experience in AI ML engineering with end-to-end pipeline development Hands-on experience building and deploying LLM RAG systems in production Strong experience with public cloud platforms AWS Azure or GCP Technical Skills Proficient in Python and libraries such as Transformers SentenceTransformers PyTorch Deep understanding of GenAI infrastructure LLM APIs and toolchains like LangChain LangGraph Experience with RESTful API development and version control using Git Knowledge of vector DBs Qdrant FAISS Weaviate and similarity-based retrieval Familiarity with Docker Kubernetes and scalable microservice design Experience with observability tools like Prometheus Grafana or Langfuse Generative AI Specific Skills Knowledge of LLMs VAEs Diffusion Models GANs Experience building structured unstructured RAG pipelines Prompt engineering with safety controls schema enforcement and hallucination mitigation Experience with prompt testing caching strategies output filtering and fallback logic Familiarity with DPO RLHF or other feedback-based fine-tuning methods Soft Skills Strong analytical problem-solving and debugging skills Excellent collaboration with cross-functional teams product QA and DevOps Ability to work in rapid-paced agile environments and deliver production-grade solutions Clear communication and strong documentation practices Preferred Qualifications Experience with OCR document parsing and layout-aware chunking Hands-on with MLOps and LLMOps tools for Generative AI Contributions to open-source GenAI or AI infrastructure projects Knowledge of GenAI governance ethical deployment and usage controls Experience with hallucination suppression frameworks like Guardrails ai Rebuff or Constitutional AI Experience and Shift Experience 5 years Shift Time 2 30 PM to 11 30 PM IST

📌 Ai / Ml Engineer/lead (Maharashtra)
🏢 Codvo.ai
📍 Maharashtra