Senior Software Engineer - Fulfillment Systems & Applied AI

Role: Senior Software Engineer - Fulfillment Systems & Applied AI

Location: Chennai, India (Remote-first, GMT-4 business hours)

Salary Range: 28 LPA - 40 LPA

A candidate with prior U.S work experience will be preferred.

Join our dynamic, small team to drive business efficiency through intelligent automation! We’re

seeking a highly skilled Senior Software Engineer to identify, design, and implement automated

solutions that reduce operational costs and enhance process performance.

Key Responsibilities:

• Analyze manual business workflows, identify automation opportunities, and collaborate with

stakeholders.

• Architect, design, and develop robust, scalable automation solutions using AI/ML techniques.

• Build, test, deploy, and maintain automation systems, ensuring seamless integration with

existing infrastructure.

• Monitor and optimize performance, troubleshoot issues, and implement enhancements for

efficiency and reliability.

• Deliver automation that reduces OPEX and enhances process robustness.

• Create and maintain clear technical documentation.

• Stay current with AI/ML and automation advancements, recommending new tools and best

practices.

Required Qualifications:

• 5+ years of professional software development experience, including senior-level

responsibilities.

• Strong programming skills in Python; experience with Java, Go, C#, or JavaScript is a plus.

• Experience with NetSuite ERP and Shopify APIs is a plus.

• Solid understanding of AI/ML fundamentals and hands-on application in process automation.

• Proven experience designing and deploying automation solutions.

• Strong analytical, systems thinking, and troubleshooting skills.

• Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent

practical experience).

• Excellent communication skills; ability to work independently and collaboratively in a small

team.

Preferred Qualifications:

• Experience with ML/DL frameworks (TensorFlow, PyTorch), NLP libraries (nltk, SpaCy), and

GenAI/LLM tools (LangChain, LangGraph, CrewAI, RAG).

• Hands-on with AWS, Azure, or GCP; familiarity with cloud-native AI/ML services and core

infrastructure (serverless, containers, managed DBs).

• Experience with workflow orchestration (Airflow) or agentic workflow frameworks.

• Proficiency in SQL, NoSQL, and vector databases.

• Understanding of DevOps, CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions, Terraform).

• Experience with Agile/Scrum methodologies.