Principal Software Engineer (Java/Go with AI)

As a Principal Software Engineer at Uniphore, you will provide technical leadership across multiple teams, driving architecture, design standards, and long-term technical strategy for large-scale, distributed, enterprise-grade SaaS platforms. You will lead the design and implementation of complex systems, mentor senior engineers, and ensure consistency and quality across multi-location teams. This role involves hands-on contribution to core components, anticipating technical challenges, and championing modern technologies to align with business goals.

Must Have

• Own and evolve the architecture of large-scale, distributed, enterprise-grade SaaS platforms.
• Drive technical vision, design principles, and architectural standards across teams.
• Lead the design and implementation of complex, high-impact systems and services.
• Partner with product, platform, and engineering leadership to align technical solutions with business objectives.
• Review and approve critical technical designs; provide guidance on trade-offs, scalability, performance, and reliability.
• Remain hands-on by contributing to core components, prototypes, and high-risk or high-complexity areas.
• Establish and enforce best practices for code quality, testing, security, and operational excellence.
• Mentor and guide senior and staff engineers, raising the overall technical bar of the organization.
• Promote high standards for availability, scalability, resilience, and delivery predictability.
• Influence Agile execution, release planning, and cross-team dependencies in multi-region environments.
• 10–15+ years of professional software engineering experience, with a strong track record of technical leadership.
• Experience leading and influencing teams across multiple regions and time zones.
• Strong analytical thinking and ability to make sound technical decisions under ambiguity.

Good to Have

• Experience with distributed data and streaming systems such as Kafka, Redis, and ClickHouse.
• Strong background in Linux-based production environments and cloud-native deployments.
• Deep knowledge of multiple database paradigms: SQL, NoSQL, time-series, graph, and vector databases.
• Experience with AI/ML platform design, including MLOps / LLMOps for large-scale production systems.
• Experience defining and implementing Service Level Objectives (SLOs), SLAs, and Service Level Management (SLM) for AI-driven services.
• Hands-on experience with LLM observability, including tracing, evaluation, monitoring, and safety/guardrails.
• Experience with LLM fine-tuning techniques such as LoRA, QLoRA, instruction tuning, or full-parameter tuning.
• Proven ability to evaluate emerging technologies and drive their adoption where they provide clear business value.

Job Description

As a Principal Software Engineer within Product Engineering, you will provide technical leadership across multiple teams and systems, driving architecture, design standards, and long-term technical strategy. You will work closely with engineering leadership, product management, and cross-functional stakeholders to translate business goals into scalable, resilient, and future-ready platforms. In this role, you remain hands-on while also influencing system design, mentoring senior engineers, setting engineering best practices, and ensuring consistency and quality across distributed, multi-location teams. You are expected to anticipate technical challenges, guide complex technical decisions, and champion modern technologies, architectural patterns, and design principles.

Responsibilities

• Own and evolve the architecture of large-scale, distributed, enterprise-grade SaaS platforms.
• Drive technical vision, design principles, and architectural standards across teams.
• Lead the design and implementation of complex, high-impact systems and services.
• Partner with product, platform, and engineering leadership to align technical solutions with business objectives.
• Review and approve critical technical designs; provide guidance on trade-offs, scalability, performance, and reliability.
• Remain hands-on by contributing to core components, prototypes, and high-risk or high-complexity areas.
• Establish and enforce best practices for code quality, testing, security, and operational excellence.
• Mentor and guide senior and staff engineers, raising the overall technical bar of the organization.
• Promote high standards for availability, scalability, resilience, and delivery predictability.
• Influence Agile execution, release planning, and cross-team dependencies in multi-region environments.

Requirements

• 10–15+ years of professional software engineering experience, with a strong track record of technical leadership.
• Expert-level programming skills in Java, Python, Go, or Rust.
• Proven experience designing and building large-scale, distributed systems and microservices-based architectures.
• Deep understanding of API design and communication protocols: REST, WebSockets, gRPC, and MCP.
• Strong hands-on experience with relational and document databases such as Postgres and MongoDB, including data modeling and performance tuning.
• Excellent grasp of data structures, algorithms, concurrency, and system design.
• Experience architecting and integrating LLM-powered systems, including RAG pipelines and vector search at scale.
• Hands-on experience with agentic frameworks such as LangChain, LangGraph, or crewAI, and designing multi-agent systems.
• Experience leading and influencing teams across multiple regions and time zones.
• Strong analytical thinking and ability to make sound technical decisions under ambiguity.

Good to Have

• Experience with distributed data and streaming systems such as Kafka, Redis, and ClickHouse.
• Strong background in Linux-based production environments and cloud-native deployments.
• Deep knowledge of multiple database paradigms: SQL, NoSQL, time-series, graph, and vector databases.
• Experience with AI/ML platform design, including MLOps / LLMOps for large-scale production systems.
• Experience defining and implementing Service Level Objectives (SLOs), SLAs, and Service Level Management (SLM) for AI-driven services.
• Hands-on experience with LLM observability, including tracing, evaluation, monitoring, and safety/guardrails.
• Experience with LLM fine-tuning techniques such as LoRA, QLoRA, instruction tuning, or full-parameter tuning.
• Proven ability to evaluate emerging technologies and drive their adoption where they provide clear business value.