Role: Engineering Manager Backend (Agentic AI)
Location: Bangalore
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) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.
Responsibilities:
- Lead and grow a team of backend engineers to build AI-native products and platforms, where intelligence, automation, and adaptability are core system capabilities.
- Drive the design and delivery of AI-powered backend systems, integrating LLMs, intelligent services, and data-driven decision layers into business workflows.
- Partner with Product, Design, and Business stakeholders to define and execute an AI-first roadmap, identifying high-impact opportunities for automation and personalization.
- Provide architectural leadership for scalable distributed systems that incorporate AI components such as retrieval pipelines, inference services, and orchestration layers.
- Establish best practices for building with AI, including prompt engineering, evaluation frameworks, guardrails, and human-in-the-loop mechanisms.
- Own the end-to-end lifecycle of backend and AI-enabled servicesfrom design and development to deployment, monitoring, and continuous optimization.
- Drive adoption of AI-native engineering practices, including AI-assisted coding, testing, documentation, and rapid prototyping.
- Ensure reliability and performance of AI systems through observability, model monitoring, and latency optimization.
- Collaborate with data and ML teams to build and scale data pipelines, embeddings infrastructure, and vector search systems.
- Mentor engineers in AI-native system design and modern backend architecture, fostering a culture of innovation, ownership, and continuous learning.
Requirements
- Bachelor's or Master's degree in Computer Science or a related field.
- 10+ years of backend engineering experience, with recent experience as an Engineering Manager or Tech Lead managing teams.
- Proven track record of delivering AI-native or AI-powered products in production environments.
- Strong understanding of LLMs, generative AI, and modern AI application architectures (e.g., RAG, embeddings, tool usage).
- Experience integrating AI capabilities into microservices and distributed systems.
- Solid hands-on background in Java, Spring Boot, and backend system design, with the ability to guide technical decisions.
- Experience with AI/ML tools, model APIs, and orchestration frameworks.
- Strong expertise in data systems (RDBMS, NoSQL) and familiarity with vector databases and large-scale data pipelines.
- Experience with cloud platforms (AWS preferred) and building scalable, cloud-native systems.
- Familiarity with Kafka, event-driven systems, and real-time data processing.
- Strong understanding of system performance, observability, and reliability engineering.
- Demonstrated ability to hire, mentor, and scale high-performing engineering teams.
- Strong ownership mindset with the ability to balance technical depth and people leadership.
- Experience in domains like eCommerce, manufacturing, or supply chain with AI-driven use cases is a plus.
