Lead AI Full Stack Developer
We are seeking a Lead AI Full Stack Developer to serve as technical anchor and people leader for a high-performing AI teams.
This role combines deep technical contribution with hands-on leadership — setting technical direction, establishing engineering standards, mentoring developers, and personally driving the most complex aspects of AI SDLC and building complex Gen AI solutions. The ideal candidate brings a rigorous Computer Science foundation, mastery-level programming, proven LLM expertise, and command of AI-augmented development practices at scale.
Responsibilities
- Define the technical direction, architecture and engineering standards for AI-enabled SDLC in collaboration with the Solution Architect and CTO
- Lead the design and implementation of AI systems including RAG pipelines, multi-agent platforms and full-stack AI applications
- Contribute hands-on to development by building complex components and conducting code reviews
- Evaluate and select technologies, frameworks, models and cloud services with a focus on reliability, security and cost efficiency
- Establish and enforce coding, testing, documentation and AI tool usage standards across the engineering team
- Mentor and support AI Full Stack Developers through feedback, guidance and career development
- Drive project planning, technical estimation and risk management
- Communicate technical solutions and trade-offs clearly to stakeholders
Requirements
- 8+ years of software development experience including 2+ years in a leadership role
- Bachelor’s degree in Engineering or related field; Master’s or PhD is a strong advantage
- Strong foundation in computer science fundamentals such as data structures, algorithms, distributed systems and system design
- Proficiency in at least one primary programming language (Python preferred) such as Python, TypeScript/JavaScript, Java, C# or Go
- Experience with software architecture and design principles including microservices, event-driven architecture, CQRS, SOLID and domain-driven design
- Experience designing APIs (REST, GraphQL, gRPC) and building full-stack applications
- Experience with relational, non-relational and vector databases
- Hands-on experience with AI systems including RAG architectures, LLM frameworks (LangChain, LlamaIndex) and agent-based platforms
- Experience with cloud platforms (AWS, Azure or GCP), Docker, Kubernetes, CI/CD and infrastructure as code
- Self-starter with ability to drive initiatives independently and elevate team performance
Nice to have
- Experience with LLM fine-tuning and open-source ecosystems (Hugging Face, vLLM, Ollama)
- Familiarity with LLM evaluation and observability tools (RAGAS, LangSmith, Weights & Biases)
- Experience with event-driven systems, Kafka, RabbitMQ or graph databases
- Exposure to multimodal AI applications (vision, audio, document processing)
- Open-source contributions, SDK/platform development or familiarity with AI governance frameworks
