Lead Developer

Job Type

Full-time

Description

We are seeking a Lead Developer with expertise in AI/ML/LLM system design and cloud-native architectures to lead the design, development, and delivery of scalable AI-powered applications. This role will play a critical part in architecting end-to-end solutions that leverage modern LLM frameworks, agentic AI, and cloud infrastructure, while partnering closely with engineering and product teams from concept through production.

Key Responsibilities

Architect, design, and deliver AI/LLM-powered cloud-native applications from initial concept through production deployment.

Design and implement Retrieval-Augmented Generation (RAG) pipelines, including integration with vector databases.

Lead architectural decisions for agentic AI systems, including deployment, orchestration, and scalability.

Develop and maintain architecture diagrams, technical design documents, and AI/ML white papers.

Build and deploy applications on Kubernetes-based cloud platforms, ensuring reliability, scalability, and security.

Lead development across teams, work with inter-org development teams, build and test solutions for release to customers.

Collaborate with cross-functional teams to translate business requirements into robust technical solutions.

Work with large datasets, including data preparation, model training, and fine-tuning workflows.

Evaluate and integrate emerging AI technologies, tools, and protocols into the platform architecture.

Ensure best practices across cloud infrastructure, AI governance, observability, and performance optimization.

Work with teams in the US, Europe and India and comfortable working different timezones.

Support triaging customer bugs and fixes.

Requirements

Required Qualifications

5+ years of experience in software engineering, systems architecture, or a related technical role, with hands-on experience designing, developing and delivering AI/LLM-driven, cloud-native applications.

Proven experience building cloud-native applications deployed on Kubernetes.

Hands-on experience designing and implementing RAG pipelines and working with vector databases.

Experience using MCP or A2A protocols.

Experience building and deploying agentic AI agents in production environments.

Strong background working with large datasets, including model training and fine-tuning.

Proven track record of delivering applications end-to-end, from design through production.

Nice to Have

Experience building highly scalable SaaS platforms.

Exposure to multi-tenant architectures and enterprise-grade AI solutions.

Experience working in cross-functional or distributed engineering teams.