Artificial Intelligence Engineer

Job Title: AI Python Developer

Location: Gurugram, Haryana (On-Site)

Experience: 2-4 years

About the Role

AI Python Developer

In this role, you will develop intelligent systems—including RAG pipelines, conversational agents, and agentic AI workflows—that bring automation, reasoning, and intelligence to both customer-facing and internal applications.

Key Responsibilities

• Design, build, and deploy

  LLM-based applications

  using Python and Azure OpenAI Services.
• Develop

  Retrieval-Augmented Generation (RAG)

  pipelines using vector databases such as Azure Cognitive Search, Pinecone, or FAISS.
• Build intelligent agents using

  LangChain, LlamaIndex, or Semantic Kernel

  .
• Apply advanced prompting techniques:

• Chain-of-Thought (CoT)

• Tree-of-Thoughts (ToT)

• ReAct, Self-Consistency, Toolformer-style prompting

• Implement reasoning strategies for

  multi-step decision-making

  and task decomposition.
• Orchestrate

  agentic AI workflows

  , integrating tools, APIs, and business logic.
• Deploy scalable LLM services using

  Azure Functions, Docker, and serverless architectures

  .
• Monitor and optimize model performance, latency, throughput, and reliability.

Must-Have Skills

• 2–4 years

  of hands-on Python development experience.
• Proven experience integrating

  Azure OpenAI (GPT models)

  into real-world applications.
• Strong understanding of

  LLMs, embeddings, vector search, and RAG architectures

  .
• Hands-on experience with at least one LLM orchestration framework:

• LangChain

  ,

  LlamaIndex

  , or

  Semantic Kernel

• Knowledge of structured prompting and LLM reasoning techniques.
• Ability to integrate

  external APIs, cloud services

  , and business systems into LLM pipelines.
• Familiarity with

  Azure Functions, Docker

  , and cloud-native development.
• Strong debugging, optimization, and analytical skills.

Good-to-Have Skills

• Experience with

  multi-agent systems

  , agentic reasoning, or cognitive architectures.
• Background in building

  AI developer tools, automation bots, or AI assistants

  .
• Exposure to

  LLMOps

  practices (prompt versioning, monitoring, evaluation).
• Familiarity with traditional

  NLP tasks

  such as summarization, Q&A, and classification.
• Experience with experimental prompting styles (reflection prompting, zero-shot CoT, role prompting, etc.).

Qualifications

• Bachelor's degree in

  Computer Science, Engineering, or a related field

  .
• 2–3 years of software engineering experience with a strong focus on

  AI/LLM projects

  .
• Hands-on deployment experience in

  Azure, AWS, or GCP

  .
• Passion for AI, continuous learning, and solving complex problems.