Home/Jobs/AI Software Engineer - Senior

AI Software Engineer - Senior

Cummins Inc.

Pune

5-8 years

Today

$41.0K–60.2K/yr

Full-time

Onsite

Skills Required LLM

RAG

Vector Database

LangGraph

Semantic Kernel

AutoGen

CrewAI

Python

Node.js

APIs

Microservices event-driven architectures cloud-native systems source control management

Test Automation

Description AI Software Engineer – Senior role focused on building scalable, secure, high-performing AI-powered software solutions and platforms. The position emphasizes reusable agentic AI frameworks, enterprise integrations, governance, and operational excellence.

Company: Cummins Inc.

Role: AI Software Engineer - Senior

Location: Pune, IND

Experience

- Experience developing enterprise software applications using modern software engineering practices
- Experience working in Agile development environments
- Proven experience delivering solutions through the full software development lifecycle
- Strong understanding of software architecture, design patterns, and scalable system development

Qualification

- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline, or equivalent professional experience

Responsibilities

- Design, develop, and maintain reusable agentic AI frameworks, orchestration templates, and platform accelerators
- Build shared services and libraries for agent communication, workflow orchestration, memory management, tool integration, and evaluation pipelines
- Establish standardized engineering patterns and best practices for enterprise AI solutions
- Develop scalable, secure, and maintainable software solutions throughout the software development lifecycle
- Develop and maintain MCP-compatible integrations and enterprise connectors
- Build reusable APIs, services, and integration frameworks for enterprise platforms and business applications
- Enable secure and scalable access to enterprise data sources, systems, and business tools
- Design and implement event-driven and cloud-native integration architectures
- Define and implement governance standards for enterprise AI systems
- Build mechanisms for traceability, auditability, monitoring, lifecycle management, and operational oversight
- Support Trust, Risk, Security, and Monitoring requirements across AI solutions
- Ensure adherence to security, privacy, compliance, and regulatory requirements throughout the development lifecycle
- Establish observability,



evaluation, and monitoring practices for responsible AI deployment
- Analyze business requirements and translate them into scalable technical solutions and architectures
- Design application interfaces, define system interactions, and establish non-functional requirements
- Evaluate technical feasibility, define solution architectures, and recommend implementation approaches
- Develop software following coding standards, testing practices, and quality assurance processes
- Participate in code reviews, testing, deployment, and production support activities
- Document solutions, technical designs, workflows, and implementation standards
- Create reusable templates, starter kits, deployment accelerators, and implementation guides
- Improve developer productivity through automation, tooling, and standardized development practices
- Support production readiness, monitoring, telemetry, guardrails, and fallback strategies
- Collaborate with solution teams to improve system reliability, scalability, maintainability, and performance
- Contribute to continuous improvement initiatives and adoption of modern engineering practices
- Stay current with emerging technologies, AI frameworks, and industry trends
- Recommend innovative approaches, tools, and technologies that improve business outcomes
- Support Agile, DevSecOps, and continuous delivery practices
- Mentor team members and contribute to the organization's technical excellence and learning culture

Additional Responsibilities

- Strong backend development experience using Python and/or Node.js
- Experience with APIs, microservices, event-driven architectures, and cloud-native systems
- Deep understanding of software development best practices including coding standards, code reviews, source control management, automated testing, CI/CD pipelines, and production operations
- Experience building enterprise AI and agentic AI solutions
- Expertise with one or more AI frameworks: LangGraph, Semantic Kernel, AutoGen, CrewAI
- Robust understanding of AI orchestration frameworks and AI system architecture




- Experience developing workflow automation, tool orchestration, and multi-agent systems
- Familiarity with MCP ecosystem concepts and enterprise AI integration patterns
- Strong understanding of AI governance, security and compliance principles, observability and monitoring frameworks, evaluation and testing methodologies, and operational risk management
- Experience implementing monitoring, telemetry, logging, and audit capabilities
- Knowledge of enterprise security and compliance requirements
- Experience with Agile, DevOps, and DevSecOps methodologies
- Understanding of CI/CD pipelines, Infrastructure as Code, and automated testing frameworks
- Ability to apply modern engineering practices that improve delivery speed, quality, and reliability
- Experience in large-scale enterprise environments

Nice To Have

- Experience with enterprise governance and risk management frameworks
- Familiarity with AI risk management, responsible AI, and compliance practices
- Experience in platform engineering and developer enablement
- Relevant technical certifications in cloud, software engineering, AI, or architecture disciplines

More Skills AI governance, security and compliance principles, observability and monitoring frameworks, evaluation and testing methodologies, operational risk management, monitoring, telemetry, logging, audit capabilities, Agile, DevOps, DevSecOps, CI/CD pipelines, Infrastructure as Code (IaC), automated testing frameworks, platform engineering, developer enablement, Retrieval-Augmented Generation (RAG), enterprise search architectures, knowledge management systems, cloud, software engineering, AI, architecture

Prepare for this role

Recommended resources to build the skills for this position. Sponsored.

Top 10 RAG Quick-Prep Questions

Zenaique A shorter RAG interview prep set for quick review.

Top 20 LLM System Design Questions (Quick)

Zenaique A focused LLM system design interview question set.

Top 50 LLM System Design Interview Questions

Zenaique

Curated LLM system design questions from Zenaique.

More LLM jobs

Senior Software Engineer -AI

Thomson Reuters

Bengalore

Today

AI/ML Data Science / Gen AI

Cognizant

Chennai

Today

Lead I - ML Engineering

UST

Thiruvananthapuram

Today

AI Engineer

Cornerstone

Hyderabad

Today

Senior Applied AI Engineer

Conqr AI

India

Today

Senior AI Engineer - Manager

Vialto

Bengalore

Today

📌 AI Software Engineer - Senior (Pune)
🏢 Top Gen AI Jobs
📍 Pune