Senior Software Engineer AI - Connectivity

Responsibilities

• Agentic Frameworks and Production Engineering: Develop reusable components for agent orchestration, context engineering, RAG, memory, tool use, MCP integration, multi-agent workflows, and human-in-the-loop controls. Design and build secure, maintainable, production-grade AI agents and services in Python, from prototype through deployment and operations.
• Connected Product and System Integration: Apply AI to connected assets, telematics, embedded systems, device lifecycle management, remote services, and engineering workflows, integrating approved enterprise systems, APIs, documentation, and connectivity data while enforcing identity, access, and data-protection requirements.
• Evaluation, Reliability, and Value Measurement: Create evaluation datasets, acceptance criteria, automated tests, tracing, and observability for agent behavior, retrieval quality, latency, and reliability. Measure gains in engineering productivity, troubleshooting, service responsiveness, quality, time, and cost to guide continued investment.
• Technical Leadership and Responsible AI: Serve as Connectivity s technical point of contact for agentic AI, establishing reference architectures and engineering practices teams can adopt consistently. Partner with enterprise architecture, cybersecurity, privacy, legal, and AI governance teams to ensure secure, auditable, and responsible AI patterns.

Required Qualifications

• Bachelors or masters degree in computer science, engineering, or a related field
• 10+ years of professional software development experience, including at least 2 years of hands-on work with AI, generative AI, or agentic AI systems
• Hands-on experience building Generative AI or LLM-based applications using RAG, tool calling, agent orchestration, or similar patterns
• Experience taking software or AI solutions from prototype through production deployment and support
• Experience with Git, modern CI/CD practices, and automated software testing

Considerations for Top Candidates

• Experience bringing LLM capabilities into production applications, including RAG and vector search
• Experience building or configuring specialized AI software-engineering agents and agentic workflows
• Experience with frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, or similar technologies
• Experience with high-volume asynchronous, event-driven, or batch processing systems
• Experience with Azure, AWS, or GCP and cloud-native AI services, plus Docker, Kubernetes, and infrastructure-as-code
• Experience evaluating or deploying open-weight or locally hosted AI models
• Experience with IoT, telematics, connected equipment, or industrial digital platforms, and connectivity technologies such as MQTT and device-to-cloud communication

Location: Chennai, India

Domestic Relocation: Yes

5 days in office required

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