Sr Engineering Manager

Job Description

This role requires deep expertise in distributed systems, high-throughput data pipelines, cloud-native architectures, and AI-driven automation, combined with the ability to drive execution across production systems and customer deployments. You will own end-to-end delivery from architecture and implementation to production rollout while working closely with POC teams, customer engineering, and product to translate real-world requirements into scalable platform capabilities. The core responsibilities for the job include the following: Technical Leadership and System Architecture: - Lead design and implementation of distributed, event-driven systems for high-scale data ingestion, transformation, and routing. - Architect low-latency, high-throughput pipelines using streaming technologies (Kafka or equivalent). - Drive the development of microservices-based architecture with a strong emphasis on scalability, resiliency, and fault tolerance. - Ensure systems are designed for: Horizontal scalability, Backpressure handling, Data consistency and durability. - Review and enforce best practices in system design, concurrency, and performance optimization. AI Agents and Automation Systems: - Lead engineering efforts for building and integrating AI agents into the DataBahn platform. - Design and implement agent orchestration layers, including: Workflow execution, Tool integration, and State and context management. - Build RAG-based pipelines and integrate LLM-driven workflows for: Data transformation, Schema mapping, and Pipeline automation. - Ensure AI systems are production-grade, with a focus on latency, cost efficiency, and reliability. POC Execution and Customer Deliverables: - Own execution of customer-specific POCs, translating requirements into working solutions under tight timelines. - Work directly with customers and POC teams to: Understand data sources, schemas, and workflows. Build custom connectors and pipelines. Deliver end-to-end solutions (ingestion, transformation, delivery). - Rapidly prototype and iterate on AI agents and automation workflows for customer use cases. - Ensure POCs are productionizable and align with long-term platform architecture. Delivery Execution and Release Management: - Own sprint execution, backlog prioritization, and delivery timelines for assigned modules. - Ensure predictable and high-quality releases across platform and customer deliverables. - Drive adoption of CI/CD pipelines, automated testing, and deployment practices. - Coordinate with QA and SRE for release readiness and production validation. Production Ownership and Reliability: - Own production systems for assigned modules, ensuring: High availability and uptime, Low latency and high throughput. - Lead incident response, debugging, and RCA efforts. - Collaborate with SRE to implement: Monitoring and alerting, Observability (metrics, logs, and tracing), and Self-healing and automated recovery mechanisms. Team Leadership and Engineering Excellence: - Lead, mentor, and manage a team of engineers working on platform and customer deliverables. - Drive engineering culture focused on: Ownership and accountability, Code quality and best practices, and Continuous learning and improvement. - Conduct code reviews, design reviews, and performance evaluations. - Hire and onboard strong engineering talent. Cross-Functional Collaboration: - Work closely with: Product teams for roadmap alignment, Customer Engineering for deployment and delivery, AI teams for agent and automation integration, SRE/Platform teams for infrastructure and scaling - Translate business and customer requirements into technical execution plans. Key Outcomes / KPIs: - Successful delivery of customer POCs and production deployments. - Reduction in time-to-delivery for customer integrations. - High reliability and performance of platform systems. - Adoption and effectiveness of AI agents and automation workflows. - Improved engineering velocity and delivery predictability. - Reduction in production incidents and improved MTTR. Requirements: - 8+ years of software engineering experience. - 2+ years in engineering management or technical leadership Managerial Skills. - Proven experience in leading and scaling engineering teams (backend, platform, and distributed systems). - Strong ability to drive execution, delivery ownership, and accountability across teams. - Experience in mentoring engineers, performance management, and career development. - Expertise in sprint planning, capacity management, and release execution. - Strong cross-functional collaboration with Product, QA, SRE, and Customer Engineering teams. - Ability to manage customer-facing deliverables and POCs under tight timelines. - Data-driven approach to tracking engineering KPIs (velocity, quality, MTTR, delivery predictability). - Strong communication and stakeholder management skills across technical and business teams. Technical Skills: - Backend and Systems Engineering: Strong backend development experience (Golang preferred; Java/Python acceptable). - Expertise in building high-performance, scalable, and production-grade systems. - Distributed Systems and Architecture: Deep expertise in: Distributed systems design, Event-driven architectures, Microservices architecture, Concurrency and scalability patterns. - Data and Streaming Systems: Hands-on experience with Kafka / streaming platforms, High-throughput data pipelines, and Real-time data processing systems. - API and Service Development: Strong experience with RESTful APIs and gRPC services, API design, versioning, and performance optimization. - Cloud and Infrastructure: Experience with: Cloud platforms (AWS / Azure / GCP), Infrastructure design for scalable SaaS systems. - DevOps and Platform Engineering experience with Kubernetes, Docker, CI/CD pipelines and automation frameworks. - Performance and Reliability: Strong skills in: Debugging complex production issues, Performance tuning and optimization, and System reliability and fault tolerance. Company Summary Our story began in 2018 when some of us were still in college. While solving some of the world's most complex design problems during undergrad like self-driving cars and representing India at Hockenheimring, we realized the potential of AI. We went on to quit our jobs at some of the best AI labs in the world like Microsoft Research and Dev, Georgia Tech, and more to do the most meaningful work of our lives. Today, our algorithms run on thousands of cameras across the world empowering organizations to do more harnessing the true capacity of Artificial Intelligence. Our mission is to push the frontiers of what's possible using artificial intelligence using exceptional techniques in GPU programming, Deep Learning, and Mathematics. The name "Adagrad" comes from a mathematical optimizer that fundamentally changed the paradigm of Deep Learning introducing adaptive gradients, similar to how we envision changing how industries function through the use of AI. Why Join Us Since its inception, our core philosophy has been seeking excellence. Our version of a great workplace is not great perks, although we have many. It's about investing in a dream team of talented people who are excited to pursue ambitious shared goals. We model ourselves as being a professional sports team, not a family.

Required Skills

['Engineering Management', 'LLMs', 'Golang', 'Java', 'Python']

Additional Information

Source recruiter: Mohita Saxena Source recruiter designation: Admin Company tagline: Delivering innovative solutions via computer vision Employee count: 10 Company founded: 2018 Benefits: Employee Stock Options, Gym membership, Health Care Company tech stack: Computer Vision, Machine Learning, Python, C, MySQL, PostgreSQL, Django Website: https://www.adagrad.ai/ LinkedIn: https://www.linkedin.com/company/adagradai/about/ Instahyre score: NA Strong match: NA Accept outstation: true Company tagline: Delivering innovative solutions via computer vision Logo: https://media.instahyre.com/images/profile/base/employer/43029/889c9f663f/1588753949027.webp