Key Responsibilities Leadership :
- Drive architecture, design, and implementation of scalable and resilient systems.
- Provide hands-on guidance in system design, code quality, performance, and security.
- Collaborate with architects, ML engineers, and product managers to build AI-integrated solutions.
- Evaluate and recommend technologies, frameworks, and tools aligned with our tech strategy.
Team & People Management :
Lead, mentor, and grow a cross-functional team of backend engineers, frontend developers, QA, and DevOps.Conduct 1 : 1s, performance reviews, and growth planning to foster talent and accountability.Maintain high standards of engineering excellence through reviews, feedback, and coaching.Product Execution & Delivery :
Own sprint planning, delivery commitments, and engineering KPIs (velocity, quality, SLAs).Align engineering execution with business goals, product roadmaps, and timelines.Track and mitigate technical risks, dependencies, and blockers across the product lifecycle.Cross-functional Collaboration :
Work closely with Product, Design, ML, QA, and DevOps teams to ensure smooth delivery.Translate product requirements into detailed technical plans and delivery roadmaps.Be the technical face of engineering in stakeholder meetings and leadership reviews.Process, Quality & DevOps :
Champion engineering best practices (TDD, CI / CD, IaC, code reviews, observability).Ensure operational excellence via automation, monitoring, alerting, and postmortems.Own system SLAs, incident management, and reliability goals.Youll Be a Great Fit If You Have : Qualifications :
10+ years of total software engineering experience with at least 3 years in a leadership role.Strong hands-on background in backend engineering (Java, Node.js, Python, etc.) and cloud-native architectures Lead the technical design and development of solutions that integrate with SAP (S / 4HANA, ECC, BTP, or APIs) and enterprise platforms.Experience leading and scaling engineering teams working on high-performance, distributed systems.Exposure to DevOps practices including CI / CD, Docker, Kubernetes, infrastructure-as-code (e.g., Terraform).Familiarity with software quality metrics, test automation, code coverage, and agile delivery.Experience managing AI / ML-based or data-intensive products (or eagerness to build in this space).Preferred Qualifications :
Prior experience building or managing AI / GenAI-integrated applications or tools (OpenAI, LangChain, vector databases, embeddings).Experience with MLOps, model lifecycle, or integrating LLMs into real-world applications.Exposure to front-end and full-stack delivery is a plus (React, Angular, etc.).Startup or scale-up experience with a bias for fast, iterative product delivery.(ref : hirist.tech)