Artificial Intelligence Engineer

Valuelabs; Hyderabad; On-site; INR 2,600,000 - 5,200,000; Full time

Job summary

Valuelabs is seeking a senior AI Engineer to design, build, and deploy generative AI-powered systems in production. You’ll own the full lifecycle from ideation to monitoring, solving real-world business problems with scalable AI solutions.

You will work hands-on with LangChain, LlamaIndex, AutoGen and build cloud-agnostic pipelines using Docker, Kubernetes, and Terraform/CDK, collaborating with product, data, and DevOps teams to deliver secure and ethical AI outcomes.

Qualifications

• 5+ years of AI engineering experience in production environments.
• Hands-on experience designing and deploying AI-powered systems.
• Strong knowledge of prompt engineering and model integration.
• Experience with containerized workflows and CI/CD.

Responsibilities

• Design and implement intelligent AI agents and pipelines.
• Develop and optimize prompt strategies for accuracy and cost efficiency.
• Work with LLMs and foundation models for fine-tuning and inference optimization.
• Build and monitor production AI pipelines using observability tools and MCP ecosystems.

Skills

Generative AI

LangChain

LlamaIndex

AutoGen

MCP tools

Docker

Kubernetes

Terraform

CDK

REST APIs

gRPC

Microservices

Observability tools

Tools

LangChain

LlamaIndex

AutoGen

Docker

Kubernetes

Terraform

CDK

Job description

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).