Lead Software Engineer

Responsibilities:

• Design and build production-grade AI platform services, LLM gateways, MCP servers, and agent orchestration frameworks.
• Lead the design and implementation of Tekion's AI gateway, a unified abstraction layer for multi-provider LLM access with intelligent routing, fallback, cost optimization, token budgeting, and comprehensive observability.
• Design and implement MCP (Model Context Protocol) infrastructure.
• Design agentic AI patterns, multi-step reasoning workflows, tool orchestration, guardrails, and human-in-the-loop escalation paths.
• Take end-to-end ownership of critical platform subsystems.
• Solve complex performance bottlenecks across inference and orchestration layers.
• Mentor junior and mid-level engineers.
• Communicate and collaborate with management, product, QA, UI/UX, and AI/ML teams.
• Deliver with quality, on time, in a fast-paced start-up environment.

Requirements:

• Bachelor's/Master's in computer science or relevant fields.
• 8+ years of relevant software engineering experience.
• Strong sense of ownership.
• Excellent Java and object-oriented development skills.
• Experience in building and scaling microservices.
• Strong problem-solving skills, technical troubleshooting, and diagnosis.
• Expected to be a role model for young engineers with a strong sense of code quality and to enforce code quality within the team.
• Strong knowledge of RDBMS and NoSQL technologies.
• Experience in developing backends for enterprise systems (e-commerce/manufacturing/supply chain, etc. ).
• Excellent understanding of debugging, performance, and optimization techniques.
• Experience with Java, MongoDB, MySQL, AWS technologies, the ELK stack, Spring Boot, and Kafka.
• Experience in developing large-scale cloud-native applications.
• Strong understanding of LLM fundamentals.
• Experience with or strong knowledge of MCP (Model Context Protocol), designing tool schemas, building MCP servers, tool discovery, and integrating MCP into agentic workflows.
• Understanding of AI gateway architecture: multi-provider LLM routing, semantic caching, load balancing, token tracking, cost allocation, fallback chains, and request/response logging.
• Familiarity with agentic AI frameworks like LangChain/LangGraph, LlamaIndex, CrewAI, OpenAI Agents SDK, or similar orchestration tools.
• Experience with LLM observability and evaluation tracing (LangSmith, OpenTelemetry), LLM-as-judge evaluation, and cost and latency monitoring.
• Understanding of AI safety and guardrails, input/output validation, PII detection, content filtering, and hallucination mitigation.
• Demonstrated ability to deliver in a fast-paced environment.
• Good communication skills.