Location: Bangalore
Role: Staff Software Engineer(8-12 Years)
About Tekion:
Tekion is looking for talented Staff Software Engineers who want to be part of building next-gen AI-native business applications on the cloud. You will use your passion and expertise for creating world-class AI platform products. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills.
Key Responsibilities :
- Lead the technical vision and architecture for Tekion's AI Native Platform — the foundational layer powering AI capabilities across all Tekion products
- Architect and build Tekion's AI gateway — a highly available, multi-provider LLM abstraction layer Lead the design of Tekion's MCP (Model Context Protocol) ecosystem
- Design and implement agentic AI frameworks
- Drive AI platform reliability and observability
- Provide technical mentorship and set engineering standards for the AI Native Platform team
- Take end-to-end ownership of platform architecture decisions and be responsible for their success in production
- Collaborate with product, AI/ML research, and domain engineering teams to define the AI platform roadmap
- Deliver with quality, on time, in a fast-paced start-up environment
Skills & Qualifications :
- Bachelor/Master's in Computer Science or relevant fields
- 8+ years of relevant software engineering experience
- Strong sense of ownership and technical leadership
- Excellent Java and object-oriented development skills
- Deep experience in building and scaling microservices
- Strong problem-solving skills, technical troubleshooting, and diagnosing
- Expected to be a role model for engineers, enforce high code quality, and drive engineering excellence within the team
- Experience in developing backends for enterprise systems (eCommerce / manufacturing / supply chain, etc.)
- Excellent understanding of debugging, performance, and optimization techniques
- Experience with Java, MongoDB, MySQL, AWS technologies, ELK stack, Spring Boot, Kafka
- Deep experience in cloud technologies and large-scale distributed systems
- Deep expertise in LLM systems — model selection and evaluation, token economics at scale, context window optimization
- Strong knowledge of MCP (Model Context Protocol) and tool-use standards — designing MCP ecosystems, tool schema governance, auth and trust models for MCP servers, and integration with multi-agent frameworks
- Experience designing AI gateways / LLM infrastructure Experience with agentic AI architectures — multi-agent systems, planning/reasoning frameworks (ReAct, Plan-and-Execute), tool orchestration, guardrails and safety layers, human-in-the-loop escalation, and agent evaluation
- Proficiency in LLM observability and MLOps Experience with AI safety, governance, and responsible AI patterns
- Demonstrated ability to deliver in a fast-paced environment
- Excellent communication and leadership skills