Principal Software Engineer

Write production-quality code regularly across core services, platforms, and AI workflows

Own and deliver high-impact features and system improvements end-to-end

Lead the modernization of legacy systems, incrementally migrating to modern, cloud-native architectures

Design, build, and evolve scalable microservices and APIs

Translate ambiguous business requirements into reliable, working software quickly

Identify technical risks early and drive pragmatic, production-ready solutions

Run complete project workstreams independently, including technical discovery, solution design, delivery planning, execution tracking, launch readiness, and post-launch follow-through

Lead the design and implementation of AI-driven development patterns, AI processing pipelines, and production-grade LLM capabilities

Build and orchestrate agentic AI systems capable of tool use, multi-step reasoning, workflow automation, task planning, and autonomous execution with appropriate human oversight

Implement MCP-style patterns (model–context–protocol or equivalent) to manage:

Context propagation

Tool invocation

State and memory

Guardrails and policy enforcement

Integrate AI systems with real business workflows, APIs, and data sources

Implement hallucination mitigation strategies, such as grounding, retrieval, validation, and structured outputs

Design evaluation, monitoring, and feedback loops for AI behavior in production

Ensure AI systems meet security, privacy, and compliance requirements

Define engineering practices for AI-assisted development, including prompt patterns, code generation workflows, review standards, evaluation criteria, and safe adoption across teams

Set and evolve architectural standards through real-world implementation

Guide service boundaries, data ownership, and integration patterns across systems

Make principled tradeoffs between speed, scalability, correctness, and cost

Act as a technical escalation point for the most challenging problems (distributed systems, data, AI workflows)

Influence technical direction across multiple teams without becoming a bottleneck

Provide full technical leadership for projects by coordinating architecture, engineering execution, dependency management, risk mitigation, and cross-team alignment

Communicate clearly with product owners, engineering leaders, security, DevOps/SRE, QA, and business stakeholders to keep delivery aligned with business outcomes

Leverage AI-powered development tools (GitHub Copilot, ChatGPT, Claude, etc.) to accelerate development

Establish best practices and guardrails for safe, high-quality AI-assisted coding

Use AI tools for solution design, refactoring, test generation, debugging, system comprehension, documentation, and accelerating high-quality delivery

Help teams adopt modern workflows that improve velocity while maintaining engineering rigor

Mentor engineers through pairing, code reviews, and design discussions

Help senior engineers grow into broader technical leadership roles

Coach less-experienced developers on modern engineering and AI-aware practices

Foster a culture of continuous learning, ownership, and technical excellence

Lead by example with clear communication, humility, and accountability

Build and maintain SaaS applications using modern frameworks and cloud platforms

Design and implement RESTful APIs and event-driven integrations

Work with relational and NoSQL databases, optimizing for performance and reliability

Build containerized applications using Docker and deploy via Kubernetes

Partner with DevOps/SRE to ensure strong CI/CD pipelines, observability, and safe deployments

Participate fully in the SDLC: design, coding, testing, deployment, and production support

10+ years of professional software development experience

Proven experience owning and delivering large, complex systems

Demonstrated success modernizing legacy systems and tech stacks

Hands-on experience designing, building, and shipping AI-driven and agentic AI systems in production or production-like environments

History of hands-on technical leadership across teams or domains

Strong track record of mentoring and developing engineers

Proven ability to lead a complete project independently, coordinate with cross-functional stakeholders, manage technical risks, and drive execution through delivery

Experience with Java or polyglot environments

Background with message queuing and event streaming (Kafka, RabbitMQ, ActiveMQ)

Deep experience with Redis or distributed caching

Frontend framework experience (React, Angular, Vue)

Experience with high-throughput or real-time AI systems

Experience building AI safety, evaluation, or governance frameworks

Strong background in Agile/Scrum environments

Bachelor’s degree in computer science or equivalent practical experience

You are consistently delivering high-impact features, including AI-powered capabilities

AI systems you build are reliable, observable, and trusted in production

Legacy systems are being systematically modernized without disrupting the business

Teams move faster because of the patterns, tools, and examples you set

Engineers seek you out for guidance on complex systems and AI design decisions

Projects you lead are well-scoped, well-communicated, and delivered through effective collaboration with product, engineering, operations, and business stakeholders

Code quality, reliability, and development velocity improve measurably

You are recognized as a technical leader who ships and elevates everyone around them