Job Opportunities API

TechGrove is the Centre of Excellence for Banyan Software, based in Chennai, India. It plays a key role in supporting Banyan’s global businesses through technology, security, and software development. TechGrove brings together India’s deep pool of technical talent with Banyan’s long-term approach to growth, creating a trusted, developer-focused environment where people can do their best work. Principal AI Engineer TechGrove AI Engineering Pod You build the intelligent features that make software feel like magic, and you make them work in production. You are equally at home shipping a clean API, standing up a RAG pipeline, evaluating an agent, or tuning guardrails so an LLM behaves safely at scale. You are excited by the current moment in AI and pragmatic about where it actually adds value. As Principal AI Engineer, you design and build the AI capabilities that differentiate an OpCo’s modernized applications: GenAI features, agentic workflows, and ML-powered functionality, integrated safely and reliably. You work side by side with the Technical Lead / Architect, contribute as a strong full-stack engineer, and help the whole pod raise its game in AI-native development. If you want to turn the frontier of applied AI into shipped, dependable product features, this role is for you. About the Pod A TechGrove AI Engineering Pod is a self-contained, AI-native software delivery team that we embed inside one of our Operating Companies (OpCos) to build, modernize, and ship production software. Each pod pairs senior engineering talent with agentic AI tooling such as Claude Code, plus the accelerators of Banyan’s AI Application Modernization Factory, to deliver at a velocity and quality bar a traditional team cannot match. A pod is typically four to eight people, and OpCos add more pods as their ambitions grow. You will work as part of a tight, high-trust team with real ownership of what you build. Pods are delivered from Banyan’s India-based TechGrove. What You Will Do Ship production AI/ML features: Design, build, and deploy GenAI integrations, agentic workflows, RAG and GraphRAG systems, and ML-powered functionality into the OpCo’s modernized applications. Orchestrate and integrate LLMs: Implement LLM orchestration, prompt and context engineering, guardrails, and evaluation to deliver reliable, safe, production-grade AI. Engineer cloud-native services: Build scalable, secure, resilient services that host and serve AI capabilities, as a strong hands-on contributor. Build agents and tooling: Develop AI agents and tooling, including building and connecting MCP servers and tools, and champion agentic development practices across the pod’s SDLC. Own data and retrieval: Design the data, retrieval, and vector or knowledge-graph infrastructure that powers GenAI features, with quality, performance, and security built in. Own technical design and quality: Lead design and implementation for AI features, write clean, well-tested code, and uphold engineering standards, security, and observability. Collaborate and mentor: Partner with the Architect and senior engineers, and coach the team on AI/ML engineering best practices. Apply pragmatic judgment: Know where AI adds real value versus risk, and navigate a fast-moving landscape with a clear head. What You Bring Experience: 8+ years in software engineering, with significant hands-on experience implementing ML/AI features in production. Production experience on AWS or Azure (required): You have designed and built cloud-native applications on AWS or Azure, including containers, serverless, and Infrastructure-as-Code (Terraform). Experience limited to GCP alone does not meet this requirement, although GCP in addition to AWS or Azure is a plus. Applied AI/ML: Demonstrated experience implementing GenAI capabilities (RAG and GraphRAG, LLM orchestration, prompt and context engineering, guardrail design) and/