Job DescriptionRole Description
We are seeking a highly skilled
Lead Software Engineer / Technical Lead to design, build, and scale cloud-native applications and AI-powered solutions. The ideal candidate will have deep expertise in Python, GCP, microservices architecture, distributed systems, and modern AI technologies including Generative AI, LLMs, RAG, and Agentic AI frameworks. This role combines hands-on engineering responsibilities with technical leadership, driving architecture decisions, mentoring team members, and delivering innovative enterprise-grade solutions that support business transformation and operational excellence.
Responsibilities- Lead the design, development, and deployment of scalable, cloud-native applications using Python and modern API frameworks such as FastAPI and Flask.
- Architect and implement microservices, distributed systems, and RESTful APIs that support high-volume enterprise workloads.
- Develop and maintain applications on Google Cloud Platform (GCP), leveraging services such as GKE, BigQuery, BigTable, Pub/Sub, and other cloud-native technologies.
- Design and manage containerized workloads using Docker and Kubernetes (GKE), ensuring scalability, reliability, and security.
- Build and optimize CI/CD pipelines to enable efficient software delivery, automated testing, and deployment processes.
- Develop event-driven architectures and streaming solutions using Kafka or similar messaging technologies.
- Design and implement robust data processing solutions utilizing SQL, BigQuery, BigTable, and large-scale data platforms.
- Lead the development and operationalization of Generative AI capabilities, including LLM integrations, RAG architectures, AI Agents, and Agentic workflows.
Qualifications- 5+ years of software engineering experience, including designing and supporting enterprise-scale applications.
- 2+ years of experience serving as a Technical Lead, Sr Engineer, or equivalent technical leadership role.
- Strong expertise in Python application development and modern API frameworks such as FastAPI, Flask, or similar technologies.
- Experience designing and implementing microservices, distributed systems, and RESTful APIs.
- Strong experience with Google Cloud Platform (GCP) and cloud-native application development.
- Hands-on experience with:
- Kubernetes (GKE)
- Docker/Containerization
- CI/CD pipelines and DevOps practices
- GitHub and modern source control practices
- Experience developing and supporting event-driven and streaming solutions using technologies such as Kafka or similar messaging platforms.
- Experience working with cloud-native data technologies including BigQuery, BigTable, SQL, and large-scale data processing solutions.
- Strong understanding of software architecture, design patterns, system reliability, performance optimization, and observability.
- Hands-on experience implementing and operationalizing:
- Generative AI solutions
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI Agents and Agentic AI workflows
- Prompt engineering and model evaluation frameworks
- Experience integrating enterprise applications with AI platforms such as Gemini, Vertex AI, OpenAI, Claude, or similar technologies.
- Strong analytical, troubleshooting, and production support skills.
- Excellent communication, collaboration, and stakeholder management skills.
