Staff Software Engineer

As a Staff Software Engineer, you will lead the design and delivery of high-impact, scalable web applications while shaping the technical direction of the team. You will serve as a trusted technical leader, driving architectural excellence, mentoring engineers, and accelerating development through AI-first engineering practices. This role requires a balance of hands-on development, system design, and cross-team influence to deliver resilient, high-quality solutions in a fast-paced, iterative environment.

• Own the design and evolution of scalable, secure, and high-performing web application architectures

• Lead complex feature delivery across systems, ensuring alignment with long-term platform strategy

• Act as a technical advisor to engineering and product leadership on design trade-offs and implementation approaches

• Drive engineering best practices across code quality, testing, observability, and system reliability

• Champion AI-powered development by actively leveraging tools (e.g., Cursor, Claude Code, LLM platforms) to enhance productivity

• Define standards and best practices for AI-assisted coding, test generation, and design-to-code workflows

• Lead adoption of generative AI and LLM integrations into enterprise applications and engineering processes

• Partner with teams to operationalize AI-driven workflows and improve development efficiency at scale

• Design, develop, and maintain full-stack web applications with a focus on performance, usability, and reliability

• Contribute high-quality, production-grade code across frontend, backend, and APIs

• Drive adoption of modern engineering practices including microservices, cloud-native development, and CI/CD

• Mentor senior and mid-level engineers, fostering technical growth and engineering rigor

• Conduct in-depth code reviews, providing actionable and constructive feedback

• Influence engineering culture by promoting collaboration, ownership, and continuous improvement

• Lead by example in driving accountability, technical excellence, and innovation

• Advanced expertise in software design, system architecture, and distributed systems

• Strong experience in API design and management (REST/gRPC, versioning, scalability)

• Deep understanding of cloud platforms (Azure or AWS) and cloud-native application design

• Solid foundation in application security, data protection, and secure coding practices

• Strong problem-solving and debugging skills across large-scale systems

• Hands-on experience integrating LLMs, generative AI, and AI APIs (e.g., OpenAI, Anthropic, Azure OpenAI, AWS Bedrock)

• Experience applying AI across SDLC: code generation, testing, documentation, and workflow automation

• Understanding of ML concepts and AI adoption strategies across engineering teams

• Proven ability to influence without authority and drive alignment across teams

• Strong communication skills, with the ability to translate complex technical concepts to diverse stakeholders

• High adaptability in fast-moving, ambiguous environments

• Commitment to ethical engineering practices and responsible AI use

• 10+ years of experience in software engineering with a strong focus on web and distributed systems

• Demonstrated success in leading complex technical initiatives and delivering at scale

• Proven track record mentoring engineers and elevating team performance

• Experience driving adoption of new technologies and engineering transformations (preferably AI-driven)

• Experience operating in iterative, product-driven environments

• Strong full-stack development experience with:

• Backend: C#, .NET, Python

• Frontend: React (or modern SPA frameworks)

• Data: SQL Server, database design, data modeling

• Deep experience with Web APIs and microservices architectures

• Hands-on experience with cloud-native development and distributed systems

• Familiarity with containerization and orchestration (Docker, Kubernetes)

• Strong understanding of DevOps practices and CI/CD pipelines

• Certifications in Cloud (Azure/AWS) or AI/ML

• Experience building enterprise-scale AI platforms or internal developer tooling

• Exposure to platform engineering, developer productivity, or internal frameworks

Originally posted on Himalayas