Senior Software Engineer

As a Senior Software Engineer, you will be a technical leader who architects and delivers complex, cloud native solutions that advance our platform transformation. You will combine deep technical expertise in cloud-native architectures with AI-augmented workflows to accelerate delivery, elevate engineering quality, and solve complex logistics and platform challenges  will tackle our most challenging technical problems and make architectural decisions that impact multiple teams and systems.

In this role, you will be an expert in GoLang, Python, React or similar modern languages, designing high-performance microservices and event-driven architectures. You will lead technical initiatives, establish patterns for AI/ML integration, and champion practices that improve system reliability, scalability, and security. You will conduct architectural reviews, elevate code quality through mentorship and rigorous code reviews, and serve as a technical resource for your team and adjacent teams.

You will have deep expertise in serverless technologies and understand how to balance innovation with operational excellence.

Your responsibilities will include owning complex technical domains, influencing engineering standards, driving incident retrospectives, and ensuring solutions meet our reliability and scalability targets. You will collaborate closely with Distinguished Engineers, architects, and product leadership to align technical decisions with business strategy. You will model a culture that values engineering excellence, scope discipline, and practical problem-solving—where "reliable, accurate, scalable, and trusted" takes precedence over theoretical perfection.

You will communicate technical concepts effectively to diverse audiences and build consensus across the organization.

• Define and lead adoption of GenAI coding workflows using tools such as Git Hub Copilot, Claude Code, Cursor, and OpenAI APIs - actively guiding, not passively accepting, AI-generated output.
• Design and operationalize agentic, multi-step workflows to automate feature development, bug triage, and documentation pipelines.
• Establish prompt engineering standards, validation frameworks, and team playbooks that ensure consistent, high-quality AI-assisted development across the organization.

• Own complex technical domains end-to-end - from design to production - with a clear line of sight to business metrics such as cycle time, defect rates, and system uptime.
• Design high-performance microservices and event-driven architectures.
• Drive measurable productivity improvements by replacing manual effort with intelligent automation at every stage of the SDLC.

• Act as the critical human-in-the-loop - rigorously reviewing AI-generated code for hallucinations, security vulnerabilities, architectural gaps, and logical flaws before they reach production.
• Apply security awareness across AI tooling (OWASP Top 10 and AI-specific attack surfaces) and enforce standards that protect system integrity.
• Conduct architectural reviews and code reviews that elevate both human-written and AI-generated contributions to production quality.

• Bachelor’s degree in computer science or a related technical field
• 5+ years of professional software engineering experience with GoLang, Python, React, or equivalent modern stack
• 3+ years of hands-on experience with AWS/Azure cloud services and serverless architectures
• Proven experience leading technical design, architecture decisions, and cross-team technical initiatives
• Demonstrated experience mentoring and coaching engineers
• Active, hands-on proficiency with at least one AI coding assistant (Git Hub Copilot, Claude Code, Windsurf, Cursor, or equivalent)

• 7+ years of professional software engineering experience
• 5+ years building enterprise-scale, cloud-native platforms
• Deep expertise with AWS serverless stack:
  Lambda, Step Functions, Event Bridge, App Sync
• Practical experience building agentic workflows using Lang Chain, CrewAI, Auto Gen, or similar frameworks
• Hands-on experience integrating AI/ML models or LLM-based agents into production workflows
• Strong background in event-driven architectures, distributed systems, and MACH architecture principles
• Experience with observability platforms, distributed tracing, and SRE practices
• Track record leading platform migrations, modernization initiatives, or post-acquisition technical integrations
• Expertise in infrastructure as code and Git Ops practices