Senior AI Engineer

Cummins; Pune District; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Cummins is seeking a senior AI engineering leader to design and deliver enterprise AI platforms. You will architect scalable AI services, work with LLMs, and build agent-based workflows in cloud environments, aligning technical decisions with business goals.

Candidates should have 8+ years in software or platform engineering and 3+ years in AI deployments, with strong Python, data pipelines, and MLOps practices.

Qualifications

• 8+ years in software/engineering or platform roles
• 3+ years deploying AI/ML solutions
• Experience delivering enterprise AI platforms

Skills

AI engineering

LLM development

Agent orchestration

Prompt engineering

RAG & retrieval

Python

REST APIs

Microservices

Distributed systems

MLOps

Agile

Leadership

Education

Bachelor/Master in CS/Engineering

Tools

LangGraph

LangChain

LlamaIndex

Hugging Face

Docker

Kubernetes

Azure OpenAI

Job description

Role & responsibilities

Technical Skills

• AI Engineering & Generative AI
  • Strong experience building, deploying, and maintaining AI-powered applications and intelligent agents.
  • Expertise in Large Language Model (LLM) application development and Generative AI solution design.
  • Experience developing agentic AI workflows, multi-agent systems, and AI orchestration frameworks.
  • Knowledge of prompt engineering, agent evaluation, guardrails, grounding techniques, and AI application observability.
  • Familiarity with Retrieval-Augmented Generation (RAG), semantic search, vector databases, and knowledge management architectures.
• Open Source AI Frameworks
  • Hands-on experience with modern AI orchestration frameworks including LangGraph, LangChain, LlamaIndex Hugging Face, Open-Source LLM ecosystems
  • Experience integrating both commercial and open-source foundation models.
  • Knowledge of model serving, inference optimization, and AI workflow orchestration patterns.
• Software Engineering & Application Development
  • Strong proficiency in Python with experience building production-grade applications and APIs.
  • Experience with modern software engineering practices including object-oriented design, design patterns, testing, and secure coding principles.
  • Experience developing REST APIs, microservices, and event-driven architectures.
  • Familiarity with front-end technologies such as React, Angular, or similar frameworks for AI application development.
  • Understanding of distributed systems and scalable application architecture.
• Data Engineering & AI Platforms
  • Experience working with Azure Databricks, Spark, and modern data platforms supporting AI workloads.
  • Strong understanding of data pipelines, feature engineering, and data preparation for AI applications.
  • Experience integrating enterprise data sources, structured and unstructured datasets, and knowledge repositories.
  • Familiarity with vector databases and embedding-based retrieval architectures.
  • Understanding of modern data lake, warehouse, and lakehouse architectures.
• Cloud, DevOps & MLOps
  • Strong experience with Azure cloud services supporting AI workloads, including:
    • Azure AI Services
    • Azure OpenAI
    • Azure Databricks
    • Azure Functions
    • Azure Kubernetes Service (AKS)
    • Azure Storage and Data Services
  • Experience with Docker, Kubernetes, and cloud-native application deployment.
  • Familiarity with MLOps and LLMOps practices including model lifecycle management, monitoring, and continuous deployment.
  • Experience implementing CI/CD pipelines using Git, Azure DevOps, Jenkins, or equivalent platforms.
  • Knowledge of AI governance, security, responsible AI, and compliance practices.
• AI Solution Architecture
  • Experience designing enterprise-scale AI platforms and reusable AI services.
  • Ability to evaluate AI technologies and recommend architecture patterns aligned with business objectives.
  • Knowledge of AI system performance optimization, scalability, reliability, and operational excellence.
  • Experience establishing engineering standards, reusable frameworks, and best practices for AI solution delivery.
    

Experience

• Minimum 8+ years of hands-on experience in Software Engineering, Full Stack Development, Platform Engineering, Data Engineering, or related technical fields.
• Minimum 3+ years of experience designing, developing, or deploying AI, Machine Learning, or Generative AI solutions.
• Demonstrated success transitioning enterprise applications from traditional software architectures to AI-enabled solutions.
• Proven experience building and deploying scalable production applications in cloud environments.
• Experience integrating AI capabilities into business applications, workflows, and enterprise platforms.
• Experience working with modern AI frameworks, LLMs, and agent-based application architectures.
• Experience operating within Agile software development environments.
• Experience collaborating with product managers, data scientists, architects, and business stakeholders to deliver innovative solutions.
• Proven ability to lead technical initiatives and mentor engineering teams.

Nice to Have

• Experience fine-tuning, evaluating, or optimizing open-source models.
• Experience with Databricks Mosaic AI, MLflow, or other enterprise AI development platforms.
• Knowledge of advanced AI techniques such as multi-agent systems, AI workflow orchestration, and autonomous agents.
• Experience with graph databases such as Neo4j and knowledge graph implementations.
• Familiarity with Deep Learning frameworks including PyTorch and TensorFlow.
• Experience building enterprise Copilots and conversational AI solutions.
• Azure AI Engineer Associate, Azure Developer Associate, Databricks, or equivalent cloud certifications.
• Understanding of Responsible AI, AI governance, and enterprise compliance requirements.