Artificial Intelligence Engineer

The Job Shop - India; Delhi; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

The Job Shop - India is seeking an experienced AI Engineer to build AI-powered products and workflows, focusing on generative AI and practical business impact.

You will design, develop, and deploy production AI applications, build RAG systems, tool-use agents, and integrate OpenAI, Anthropic, Google Gemini, and other models. Strong Python and framework expertise are required for success.

Qualifications

• 3–5 years of professional software engineering experience.
• 1–3 years building production AI applications using LLMs or Generative AI.
• Strong proficiency in Python and modern AI tooling.
• Experience with LangChain/LangGraph/LlamaIndex and related frameworks.
• Experience with RAG architectures and vector databases.
• Experience integrating LLM APIs (OpenAI, Anthropic, Google Gemini).
• Strong prompt engineering, tool calling, and API integration skills.
• Experience with REST APIs and cloud platforms, plus Docker/Git/CI/CD.

Responsibilities

• Design, develop, and deploy production-grade AI applications using modern LLMs.
• Build Retrieval-Augmented Generation systems with embeddings and vector databases.
• Develop intelligent agents capable of tool use, function calling, and orchestration.
• Integrate OpenAI, Anthropic, Gemini, and other foundation models.
• Evaluate models, frameworks, and prompts to improve quality and cost.
• Build APIs and backend services exposing AI capabilities.
• Develop evaluation pipelines and automated testing for prompts and agents.
• Implement observability, guardrails, and production monitoring.
• Partner with stakeholders to identify AI improvements for processes and experiences.
• Contribute to AI architecture decisions and engineering best practices.
• Stay current with evolving AI ecosystem and drive innovation.

Skills

Python

LangChain

LangGraph

LlamaIndex

Semantic Kernel

DSPy

Prompt engineering

REST APIs

Cloud platforms

Docker

Git

CI/CD

Tools

Pinecone

Weaviate

Milvus

Chroma

pgvector

Job description

We're looking for an experienced AI Engineer to help build the next generation of AI-powered

products and workflows. This role is focused on applying the latest advances in generative AI—

not training foundation models—to solve real business problems.

What You'll Do

• Design, develop, and deploy production-grade AI applications using modern LLMs and
• Build Retrieval-Augmented Generation (RAG) systems leveraging embeddings, vector databases, hybrid search, and knowledge retrieval.
• Develop intelligent agents capable of tool use, function calling, workflow orchestration, and autonomous task execution.
• Integrate commercial and open-source foundation models including OpenAI, Anthropic, Google Gemini, and others.
• Evaluate new models, frameworks, and prompting strategies to improve quality, reliability, latency, and cost.
• Build APIs and backend services that expose AI capabilities to internal and external applications.
• Develop evaluation pipelines and automated testing for prompts, agents, and AI workflows.
• Implement observability, monitoring, guardrails, and feedback mechanisms for AI systems in production.
• Partner with stakeholders to identify opportunities where AI can improve business processes and employee experiences.
• Contribute to AI architecture decisions, coding standards, and engineering best practices.
• Stay current with the rapidly evolving AI ecosystem and help drive technical innovation across the organization.

Required Qualifications

• 3–5 years of professional software engineering experience.
• 1–3 years building production applications utilizing Large Language Models or Generative AI technologies.
• Strong proficiency in Python.
• Experience developing AI applications using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, DSPy, or similar.
• Experience implementing RAG architectures and working with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or pgvector.
• Experience integrating LLM APIs including OpenAI, Anthropic, Google Gemini, or similar platforms.
• Strong understanding of prompt engineering, structured outputs, tool calling, and function invocation.
• Experience building REST APIs and integrating AI capabilities into existing applications.
• Familiarity with cloud platforms (AWS, Google Cloud, or Azure).
• Experience with Docker, Git, CI/CD, automated testing, and modern software
• Strong communication skills and the ability to explain technical concepts to both technical and non-technical audiences.

Preferred Qualifications

• Experience building autonomous or multi-agent systems.
• Experience using AI evaluation frameworks such as LangSmith, Arize Phoenix, Weights & Biases, Promptfoo, or DeepEval.
• Experience with MCP (Model Context Protocol), A2A (Agent-to-Agent communication), or emerging AI interoperability standards.
• Experience with multimodal AI including image, video, speech, or document
• Experience deploying open-source models using vLLM, Ollama, Hugging Face, or similar inference platforms.
• Familiarity with Kubernetes and scalable cloud infrastructure.
• Background in MLOps, feature engineering, or traditional machine learning.
• Experience building internal AI products, developer tools, or workflow automation platforms.

What Success Looks Like

Within your first year, you'll have:

• Built and launched production AI applications used across the organization.
• Improved existing AI products through experimentation and evaluation.
• Established reusable patterns for agents, RAG systems, and prompt engineering.
• Become a trusted technical partner for engineering and business teams.

Technologies We Use