Engineering Manager

• Key Responsibilities:
  

Technical 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.
  

You’ll Be a Great Fit If You Have

Must-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 (AWS/Azure/GCP).
• 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.