Engineering Manager

Recruit, coach, mentor, and retain top engineering talent across levels.

Run meaningful 1:1s, give clear and timely feedback, own performance and career development, and develop future leaders within the team.

Foster a culture of ownership, engineering craftsmanship, psychological safety, and continuous improvement.

Turn ambiguous product and business goals into a scoped, sequenced roadmap with a balanced portfolio of foundational investments, new capabilities, and run-the-business work.

Plan and deliver against the roadmap with clear, incremental milestones.

Drive predictable execution and hold the team to the metrics that matter — on-time delivery, quality and regression rates, incident response, and system reliability.

Own operational metrics, on-call, SLOs, and support for your services, and drive blameless postmortems that make the platform steadily more robust.

Guide architecture and technology choices for scalable, reliable, maintainable systems.

Champion strong engineering practices and processes across the full development lifecycle — design and code review, testing, source control, CI/CD, and live site operations.

Drive their adoption across the team, and manage technical debt deliberately.

Work closely with product, design, and the founding team to align on priorities and navigate technical trade-offs.

Be the voice of the customer and the product within your team, translate complex technical concepts for non-technical audiences, manage expectations, and represent your team in reviews with senior leadership and, where needed, with enterprise customers.

Ensure the team understands OrbitShift's goals and how their work connects to the bigger picture.

You'll lead a team working across a modern backend and data stack. We care more about depth in fundamentals than familiarity with any specific tool — but to give you a sense of the environment, roughly in order of how central each is to the role:

Distributed systems & micro-services. Designing, scaling, and operating service-oriented architectures — API design, and the reliability, consistency, and performance trade-offs that come with distributed systems. This is the core of the role.

Event-driven & asynchronous systems. Message queues, streaming, and event-driven patterns for decoupled, resilient data and processing pipelines.

Cloud & data infrastructure (AWS). Building and operating on AWS; containerization; relational databases (PostgreSQL); search and vector stores (OpenSearch); and solid observability, CI/CD, and infrastructure practices for production services.

AI & Agentic systems (a plus). LLM and Agentic architectures, retrieval-augmented generation (RAG), embeddings, model orchestration and routing (e.g., Amazon Bedrock, OpernRouter), and evaluation.

B.Tech / M.Tech in Computer Science or a related field, preferably from a reputed institute (IIT, BITS, NIT, or equivalent).

10+ years of software engineering experience, with at least 2 years directly managing and growing a team of engineers (hiring, performance, career development).

3+ years in a technical leadership role, overseeing the design and delivery of complex projects.

A track record of shipping and operating production systems at scale — strong system design fundamentals, distributed systems, and cloud (AWS preferred).

Experience architecting for reliability and scaling, and knowledge of full-lifecycle engineering practices: code reviews, source control, build, testing, and live site/operational health.

Demonstrated ability to deliver results and make progress in a fast-changing, ambiguous problem space, adjusting course as new information emerges.

Strong communication and stakeholder skills — able to translate complex technical concepts for non-technical audiences and align cross-functional partners.

Background in B2B SaaS or security/compliance-sensitive enterprise deployments.

Experience scaling a team or engineering org through a period of fast growth.

Comfort working in AI-assisted development workflows, with the discipline to review and understand what the AI produces.

Lead a team building real, enterprise-grade software at a fast-growing startup — systems customers run in production, not demos.

Direct line to the founding team and a seat in the decisions that shape the product and the org.

Work alongside a world-class team — engineers and operators from Amazon, McKinsey, IIT, and Stanford.

A fast growth curve, strong ownership, and competitive compensation with equity.