Principal Software Engineer at Solera Holdings, LLC. in Bangalore

Job description

• We’re looking for a hands-on Principal Software Engineer (P5) who is deeply focused on AI-driven development, agentic AI systems, and practical delivery of production software. This person will not only set the technical direction but also take full ownership of complex initiatives—leading projects from concept through architecture, implementation, launch, and continuous improvement.
• Leads complete, high-impact projects end-to-end with strong technical ownership, execution discipline, and stakeholder alignment
• Designs and builds AI-driven software solutions using LLMs, agentic architecture, MCP-style orchestration, and AI-enabled automation
• Makes pragmatic architectural decisions that balance speed, reliability, and long-term maintainability
• Leverages AI-assisted development tools to accelerate delivery and elevate team productivity
• Partners effectively with product, architecture, security, operations, and business stakeholders to turn ambiguous goals into delivered outcomes
• Mentors engineers and raises the overall technical standard through example, code review, and system ownership
• You will operate with broad autonomy, lead complete initiatives without requiring constant direction, influence architectural direction across teams, and be known as someone who ships, unblocks others, aligns stakeholders, and makes things happen.

Responsibilities

• Build, Ship, and Own
• 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
• AI-Driven Development, Agents & LLM Systems
• 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
• 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
• Technical Leadership & Architecture
• 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
• AI‑Assisted Engineering & Developer Productivity
• 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
• Mentorship & Team Elevation
• 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
• Technical Execution & Operations
• 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

Requirements

• Experience
• 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
• Technical Skills
• Expert-level proficiency in C# and .NET (ASP.NET Core, modern .NET)
• Deep understanding of RESTful API design and distributed systems
• Strong experience with microservices architectures
• Agentic AI architectures and autonomous workflow execution
• Tool/function calling
• Context and memory management
• AI workflow orchestration (e.g., MCP-style patterns)
• Experience integrating AI systems with datastores, APIs, and event-driven workflows
• Hands-on experience with relational databases (SQL Server, PostgreSQL)
• Working knowledge of NoSQL data stores and caching strategies (e.g., Redis)
• Strong experience with Docker and production containerization
• Practical experience with Kubernetes and container orchestration
• Comfort working in cloud environments (AWS and/or Azure)
• Proficient with Git and modern development workflows
• Strong understanding of testing strategies and production-quality code
• Strong proficiency in C# and .NET, including ASP.NET Core and modern .NET development
• Frontend framework experience such as React(Preferable)
• , Angular
• Hands-on experience with relational databases such as SQL Server
• Hands-on experience with LLMs, AI workflow orchestration, or agentic AI patterns, including tool/function calling, context management, structured outputs, and workflow state
• Develop production-quality code across distributed services and architecture, leveraging expertise in APIs, workflow orchestration, and AI-enabled solutions.
• Bachelor’s degree in computer science or equivalent practical experience
• Experience with Python, Java, TypeScript, or polyglot engineering environments
• Experience with message queues, event streaming, or workflow orchestration platforms
• Experience with vector databases, retrieval-augmented generation, knowledge graphs, or semantic search
• Experience building AI evaluation harnesses, prompt/version management, safety checks, or governance workflows
• Background with high-throughput, real-time, or operationally critical SaaS systems
• Strong background in Agile/Scrum environments and cross-functional delivery

Skills

Required

• Strong technical ownership
• Execution discipline
• Stakeholder alignment
• Pragmatic architectural decision-making
• Clear communication
• Humility
• Accountability
• Autonomy
• Influence across teams
• Problem-solving
• Continuous learning
• C#