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 up-to-date 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.

📌 Senior AI Engineer (Pune)
🏢 Cummins
📍 Pune