Job
Description
Qualifications: Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Technical Expertise: Proven experience in Python development, with a strong grasp of frameworks and libraries such as Pydantic and FastAPI. Hands-on experience with cloud platforms (AWS, Azure) and modern DevOps practices. Demonstrable experience working with GenAI technologies: LLM Models : Working knowledge of models like GPT-3/GPT-4, Anthropic’s Claude, and Meta's LLaMA. Vector Databases : Experience with solutions like Pinecone, Weaviate, Milvus, or Faiss. Agentic Frameworks : Familiarity with Autogen and its alternatives (e.g., LangChain, ReAct-based frameworks). Expertise in designing clean, modular, and maintainable code, with a deep understanding of design patterns and best practices. Leadership & Mentoring: Prior experience as a technical lead or senior developer with a focus on guiding teams through complex technical challenges. Strong communication skills, with the ability to clearly articulate technical concepts and foster a collaborative environment. Desirable Skills: Familiarity with containerization (Docker, Kubernetes), CI/CD pipelines (Jenkins, GitLab CI), and microservices architecture. Experience with machine learning/deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus. What We Offer: Innovative Work Environment: A dynamic, hands-on role that emphasizes technical excellence and innovative problem-solving. Professional Growth: Opportunities to stay on the cutting edge of GenAI technology with ongoing professional development and research initiatives. Collaborative Culture: A supportive, team-oriented atmosphere where your technical expertise directly impacts the success of high-profile projects. This role is tailored for a seasoned, hands-on technical leader passionate about GenAI, with the ability to drive code excellence and mentor a diverse development team. If you thrive on solving complex technical challenges and setting high standards for software quality, we’d love to hear from you. Roles and Responsibilities Overview: We are a custom software services company specializing in cutting-edge GenAI solutions. Our projects leverage advanced technologies including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Vector Databases, and Agentic AI frameworks. We are seeking a hands-on Lead Developer to own the design, structure, and quality of our codebase, while organizing development tasks and deliverables for a team of skilled developers. Key Responsibilities: Technical Ownership & Hands-On Development: Own the architectural design and structure of GenAI applications, ensuring robust, scalable, and maintainable code. Champion best practices for code quality, maintainability, and the use of design patterns. Be actively involved in coding, code reviews, and mentoring other developers to uphold technical excellence. Technical Leadership & Task Organization: Organize and prioritize development tasks and deliverables, ensuring that technical challenges and blockers are swiftly addressed. Lead technical discussions and brainstorming sessions to design solutions that meet both current and future business needs. Coordinate with team members to ensure clear responsibilities and streamlined development processes without heavy project management oversight. Solution Architecture & Implementation: Design and implement high-quality solutions using Python, modern frameworks (e.g., Pydantic, FastAPI), and industry-standard development practices. Integrate on cloud platforms such as AWS and Azure, ensuring the seamless deployment of GenAI applications with scalable and secure architectures. Evaluate and incorporate advanced AI technologies: LLM Models : Examples include OpenAI's GPT-3/GPT-4, Anthropic's Claude, Meta's LLaMA, and others. Vector Index Technologies : Examples include Azure AI Search, Pinecone, Weaviate, Milvus, and Faiss. Agentic AI Frameworks : Utilize frameworks like Autogen, as well as alternatives such as LangChain or ReAct-based solutions. Continuous Improvement & Innovation: Stay current with emerging GenAI trends, tools, and frameworks, and proactively integrate these into our solutions. Continuously refine the development process by advocating for improvements in code reviews, automated testing, and continuous integration/deployment practices. Cross-Functional Collaboration: Work closely with other technical teams to align on architecture decisions and share best practices. Communicate technical concepts effectively to both technical peers and non-technical stakeholders when necessary.
