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AI Engineer

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Summary

Senior AI developer role in Chennai building LLM-powered solutions (copilots, agentic workflows, RAG pipelines) on Azure Databricks, along with Python/PySpark data pipelines and Python microservices. Targets ~8-10 years of experience with full ownership of deliverables and minimal supervision.

AI Developer – Azure Databricks, Python, Java, Microservices & AI (LLM/Copilot or Equivalent )


Job Summary

We are looking for a AI Developer with strong expertise in Python, Azure Databricks (ADB), Delta Lake, and AI/LLM technologies to design and build Databricks jobs, reusable scripts, and cloud-native microservices. The role requires hands-on experience with Copilot agentic mode (or equivalent), building LLM-driven AI use cases, and the ability to work independently by taking full ownership of deliverables without the need for micromanagement.


Roles and Responsibilities

Azure Databricks & Data Engineering

  • Design, develop, and manage Azure Databricks jobs, workflows, and notebooks.
  • Build reusable Python/PySpark scripts for data ingestion, transformation, and analytics.
  • Implement Delta Lake–based lakehouse architectures with ACID transactions and versioning.
  • Optimize Databricks workloads for performance, scalability, and cost efficiency.
  • Implement batch and streaming pipelines using Databricks.

Microservices & Application Development

  • Develop Python-based microservices to expose data and AI capabilities via APIs.
  • Build and integrate RESTful services for data access, AI inference, and orchestration.
  • Ensure secure, scalable, and resilient service design using cloud-native patterns.
  • Drive development tasks independently, from design through deployment, with minimal supervision.

AI, LLMs & Copilot Agentic Mode

  • Design and build LLM-powered AI use cases such as copilots, intelligent assistants, and automation agents.
  • Implement Copilot agentic mode workflows, including tool calling, task planning, and multi-step reasoning.
  • Develop prompt engineering strategies, system prompts, and guardrails for enterprise use.
  • Integrate LLMs with Databricks, data lakes, and microservices for real-time and batch inference.
  • Build RAG (Retrieval-Augmented Generation) pipelines using enterprise data.
  • Evaluate, fine-tune, and monitor LLM performance, accuracy, and cost.

Architecture, Governance & Best Practices

  • Contribute to solution architecture and technical design decisions.
  • Ensure data security, governance, and compliance in data and AI solutions.
  • Implement logging, monitoring, and observability for Databricks jobs and AI services.
  • Perform code reviews and enforce engineering best practices.

Leadership & Collaboration

  • Mentor peer developers and provide technical guidance when needed.
  • Collaborate effectively with data scientists, architects, DevOps teams, and business stakeholders.
  • Clearly communicate technical concepts, progress, and risks through excellent verbal and written communication skills.
  • Take full ownership of assigned workstreams and drive them to completion without requiring micromanagement.

Required Technologies & Skills

Programming & Frameworks

  • Python (advanced)
  • PySpark / Spark SQL
  • REST APIs and microservices frameworks (FastAPI, Flask, etc.)

Azure & Data Platforms

  • Azure Databricks (ADB)
  • Delta Lake
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure cloud services and security fundamentals

AI / LLM & Copilot

  • Hands-on experience with LLMs (Azure OpenAI, OpenAI, or similar)
  • Experience building Copilot solutions and agentic workflows
  • Prompt engineering and orchestration frameworks (LangChain, Semantic Kernel, etc.)
  • Experience with RAG architectures, vector databases, and embeddings
  • Understanding of AI safety, guardrails, and responsible AI practices

DevOps & Engineering

  • CI/CD pipelines (Azure DevOps, GitHub Actions)
  • Git version control
  • Containerization (Docker preferred)
  • Infrastructure-as-code concepts (Terraform/Bicep – preferred)

Preferred Qualifications

  • 8 to 10 years of experience in Python, data engineering, or backend development
  • Proven experience delivering production-grade AI/LLM solutions
  • Experience in enterprise-scale cloud environments
  • Exposure to streaming platforms (Kafka, Event Hubs – preferred)

Soft Skills

  • Excellent verbal and written communication skills
  • Strong sense of ownership and accountability
  • Ability to work independently and proactively drive outcomes
  • Strong problem-solving and analytical skills
  • Collaborative mindset with leadership capabilities


Skills

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See also

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