We're seeking a senior AI Engineer with 5+ years of experience who thrives at the intersection of Generative AI, intelligent agents, and real-world application delivery.You'll be responsible for designing, building, and deploying next-generation AI-powered systems that solve complex business problems - from automating workflows to creating intelligent decision-making agents.This is not a research-only role.You'll own the full lifecycle : ideation - prototyping - model selection - prompt engineering - integration - deployment - monitoring - all in production.Roles and Responsibilities :- Design and implement intelligent AI agents using frameworks like LangChain, LlamaIndex, AutoGen, or custom agent architectures.- Develop and optimize prompt engineering strategies for accuracy, consistency, and cost efficiency across diverse use cases.- Work with large language models (LLMs) and foundation models (e.g., Llama, Mistral, GPT, Claude) - fine-tuning, RAG, and inference optimization.- Leverage MCP (Model Control Platforms) tools (e.g., PromptLayer, Weights & Biases, Arize, LangSmith) for observability, testing, and governance.- Build cloud-agnostic AI pipelines using containerization (Docker), orchestration (K8s),



and infrastructure-as-code (Terraform/CDK).- Integrate AI components into existing systems using REST/gRPC APIs, event-driven architectures, and microservices.- Collaborate with product, data, and DevOps teams to deliver scalable, secure, and ethical AI solutions.- Stay ahead of the curve: evaluate new models, tools, and frameworks (e.g., multimodal AI, reasoning models, tool use).Key Skills :- Strong programming skills in Python and experience developing production-grade applications.- Hands-on experience with Generative AI, LLMs, and foundation models such as GPT, Claude, Llama, and Mistral.- Proficiency in AI agent frameworks such as LangChain, LlamaIndex, and AutoGen.- Solid understanding of RAG architectures, embeddings, vector databases, semantic search, and retrieval optimization.- Experience with prompt engineering, tool calling, multi-agent orchestration, and Model Context Protocol (MCP).- Familiarity with LLM evaluation and observability tools such as LangSmith, Arize, PromptLayer, and Weights & Biases.- Experience with REST APIs, gRPC, microservices, Docker, Kubernetes, and Terraform.- Knowledge of cloud platforms such as AWS, Azure, or GCP, along with AI security, performance optimization, and production deployment practices. (ref:hirist.tech)

📌 ValueLabs - Senior Artificial Intelligence Engineer (Hyderabad)
🏢 ValueLabs
📍 Hyderabad