Key job responsibilities :

As a Principal AI Software Engineer, you will drive technical strategy and excellence across multiple initiatives while leading complex AI system development.

Strategic Technical Leadership :

- Define and drive technical vision and architecture for AI-native applications across multiple product areas

- Act as an enabler for successful execution of identified projects

- Lead cross-functional technical initiatives, collaborating with engineering leadership, product management, and data science teams

- Establish technical standards, design patterns, and best practices for AI-augmented development across the organization

- Drive technical decision-making for complex systems that span multiple teams and products

- Make decisions with confidence when problems or solutions are not well defined

- Manage risk and uncertainty for self and team within a dynamic priority-setting environment

- Contribute as a thought leader within the team, and help to refine current state as well as future state plans and product roadmaps

Advanced AI Systems Architecture :

- Design and architect enterprise-scale full stack applications with sophisticated AI integrations across natural language processing, computer vision, and predictive analytics

- Lead the development of complex, multi-tenant AI systems serving millions of users with high availability and performance requirements

- Architect advanced RAG (Retrieval-Augmented Generation) systems, agentic workflows, and autonomous AI architectures

- Design cost-efficient, scalable LLM integration strategies across multiple providers with advanced optimization and failover mechanisms

- Establish frameworks for AI model evaluation, A/B testing, and performance optimization at enterprise scale

Cross-Team Technical Influence :

- Drive adoption of emerging AI technologies and evaluate their strategic impact on product development

- Lead technical due diligence and integration planning for major AI technology decisions

- Collaborate with external partners, vendors, and research institutions on cutting-edge AI initiatives

- Establish monitoring, observability, and cost management frameworks for AI systems across the organization

- Contribute to open source projects and represent the company at technical conferences and industry events

Engineering Excellence & Innovation :

- Champion engineering best practices including comprehensive testing, code quality, security, and scalability standards

- Expert in Agile Development

- Lead investigation and proof-of-concept development for emerging AI technologies and methodologies

- Drive technical innovation initiatives that differentiate our AI capabilities in the market

- Establish and maintain technical documentation, architectural decision records, and knowledge sharing practices

- Lead incident response and post-mortem processes for complex AI system issues

REQUIRED QUALIFICATIONS :

- Masters Degree in Electrical, Computer Science, Computer Engineering, Robotics or related field

- 10+ years of non-internship professional software development experience

- 12+ years of programming using JavaScript/TypeScript and multiple backend languages (Python preferred, Node.js, Java, or Go)

- 6+ years of experience with modern front-end frameworks (React, Vue, or Angular) and advanced state management patterns

- Proven track record designing and shipping complex production applications that incorporate LLMs or AI services at enterprise scale (1M+ users)

- Advanced expertise in prompt engineering, model optimization, and deep understanding of AI system limitations and capabilities

- Demonstrated experience with agentic workflows and autonomous AI system architectures

- Extensive experience leading technical teams, driving cross-team initiatives, and providing technical mentorship

- Expert-level experience with cloud platforms (AWS, GCP, or Azure) and advanced containerization (EKS), orchestration, and infrastructure as code (GitOps)

- Strong background in system design, scalability, and performance optimization for high-traffic applications

- Must be willing to work out of an office located in Bangalore JFWTC Campus

- You must submit your application for employment on the careers page at www.careers.gevernova.com to be considered.

PREFERRED QUALIFICATIONS :

- 18+ years of full software development lifecycle experience, including architecture design, technical leadership, and large-scale system optimization

- Expert-level experience with vector databases (Pinecone, Weaviate, pgvector) and advanced embedding model optimization

- Deep expertise with multiple LLM providers and advanced AI orchestration frameworks (LangChain, LlamaIndex, custom frameworks)

- Advanced understanding of enterprise RAG architectures, semantic search optimization, and conversation memory management at massive scale

- Experience with multi-modal AI integration, model fine-tuning, and deployment of custom AI models

- Track record of building and scaling AI-powered features for 10M+ users with high availability requirements

- Expert knowledge of AI observability tools, cost optimization strategies, and performance monitoring at enterprise scale

- Master's degree or PhD in computer science, AI/ML, or equivalent advanced technical education

- Extensive experience with agent architectures, autonomous AI systems, and cutting-edge agentic workflow implementations

- Background in machine learning research, AI safety, or advanced AI system design

- Experience with technical strategy development and technology roadmap planning

Technical Stack :

- Languages : Python, TypeScript/JavaScript, SQL, Go/Rust (for performance-critical components)

- Frontend : React/Next.js, Vue.js, Advanced CSS frameworks, Progressive Web Apps, Micro-frontends

- Backend : Node.js/Express, FastAPI, PostgreSQL, Redis, MongoDB, Event-driven architectures, Microservices

- AI/ML : OpenAI API, Anthropic Claude API, Advanced LangChain implementations, pgvector, Pinecone, Custom model deployments, Advanced agentic workflow frameworks

- Infrastructure : Enterprise AWS/Azure services, Advanced Kubernetes, Service mesh, Infrastructure as Code, Multi-region deployments

- Development Tools : GitHub Copilot, Advanced AI-assisted development environments, Custom tooling and automation

- Monitoring : Enterprise observability platforms, Advanced LLM cost monitoring, Performance optimization tools, Custom analytics