Senior Software Engineer(Backend+Native AI)

Tekion Corp; Bengaluru; On-site; INR 420,000 - 640,000; Full time

Job summary

You will work across Java, microservices, and cloud technologies, mentor engineers, and collaborate with product, QA, UI/UX, and AI/ML teams to deliver high-quality solutions in a fast-paced startup environment.

Qualifications

• Bachelor’s or Master’s in Computer Science or relevant field.

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 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.

Skills

Java & OO

Microservices

LLM fundamentals

MCP protocol

Backends for enterprise

RDBMS/NoSQL

AWS & ELK

Spring Boot

Kafka

Code quality leadership

Education

Bachelor’s/Master’s in CS

Tools

MongoDB

MySQL

AWS technologies

ELK stack

Spring Boot

Kafka

Job description

Role:Senior Software Engineer(5-8 Years)

About Tekion :

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC), Automotive Enterprise Cloud (AEC), and Auto Location motive Partner Cloud (APC). Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. Tekion employs close to 3,000 people across North America, Asia, and Europe.

Key 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

Skills & Qualifications :

• Bachelor/Master's in Computer Science or relevant fields
• 5+ 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 diagnosing
• Expected to be a role model for young engineers with a strong sense of code quality and enforce code quality within the team
• Strong knowledge in RDBMS and NoSQL technologies
• 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
• 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 — LangChain/LangGraph, LlamaIndex, CrewAI, OpenAI Agents SDK, or similar orchestration tools
• Experience with LLM observability and evaluation — tracing (LangSmith, OpenTelemetry), LLM-as-judge evaluation, 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