- Understand and analyze product requirements and collaborate with product managers and architects to clarify requirements and ensure alignment.
- Design, develop and implement software features with the end user in mind. Write clean, efficient, and maintainable code to implement these features. Optimize code and model performance for efficiency and scalability.
- Develop and execute unit, integration, and system tests to ensure feature reliability. Implement automated test cases with high code coverage. Validate the performance and accuracy of integrated AI models.
- Integrate Generative AI models into the software application. Ensure that models are properly interfaced with other system components.
- Stay updated with the latest developments in AI and Machine Learning (ML) technologies to provide informed support to the team, including prompt processing, contextual grounding, actionable response generation, system prompt generation, and GenAI UI frameworks.
- Participate in code reviews to ensure code quality and consistency.
- Implement CI/CD practices to automate testing and deployment processes. Ensure that new features are seamlessly integrated into production environments.
- Collaborate with security, privacy, and governance teams to ensure that the products developed comply with relevant policies, standards, and regulations.
- Liaise with other developers, business units, product managers, engineering, and other applicable groups to ensure flawless execution
Preferred Qualifications:
- Technical Skills: Full comprehension of full stack enterprise Software Development Lifecycle and risks, knowledge of Machine Learning and GenAI, familiarity with natural language processing (NLP) techniques and libraries, search technologies, chatbot interactions, web development, database systems (e.g., ChromaDB, Postgres, Redis, Neo4j, FAISS), cloud platforms & platform services (e.g., AWS, GCP, Azure). Understanding of CI/CD pipelines and tools, knowledge of containerization technologies (e.g., Docker, Kubernetes)
- Hands-on Coding Experience: Proficiency and usage of programming languages (e.g., Python, Java, C#, GoLang, R), front-end technologies (e.g., HTML, CSS, JavaScript, TypeScript, React, Angular), back-end frameworks (SpringBoot, Fast API, Flask), GenAI Foundational frameworks (Hugging face, Embeddings, LLM models, TensorFlow, PyTorch), REST API management, database systems (e.g., SQL, NoSQL). Experience in writing clean, efficient, and maintainable code, code reviews, unit testing and coding standards, proficiency in version control systems like Git.
- Delivery of High-Quality Software Applications: Experience with software design patterns and principles, Knowledge of testing frameworks and methodologies, ability to write comprehensive unit, integration, and system tests.
- Prompt Processing Understanding: Developing efficient mechanisms for prompt processing, integrating prompt processing systems with LLMs, reprocessing data to ensure it is suitable for prompt processing, implementing solutions to support asynchronous programming, knowledge of Gen AI Frameworks/concepts (e.g., LangChain, RAG, OpenAI libraries, sentence transformers libraries)
- Contextual Grounding Knowledge: Proficiency in keyword based, semantic, and vector search techniques, skills in building and utilizing knowledge graphs to link and organize data, ability to use data mining techniques to extract useful information from large and diverse datasets, expertise in information retrieval and contextual analysis.
- Actionable Response Generation: Expertise in generating contextually relevant responses, skills in designing and optimizing prompts to guide language models effectively, ability to develop and implement mechanisms that score, and rank responses based on relevance and actionability.
- LLM Interaction Experience: Knowledge of various prompting techniques. (e.g., zero shot, few-shot, chain of thought), ability to write effective prompts to guide system behavior to drive conversation according to business expectations, knowledge in effective organization, versioning and tracking of prompts.
- User Interaction and Interface Proficiency: Knowledge of UI frameworks like React/Angular and frontend technologies like JavaScript/TypeScript, knowledge of building user interfaces, proficiency in design tools like Figma.
- Agile Development Proficiency: Proficiency in Agile methodologies. experience working in cross-functional teams, proficiency in tools like JIRA.
- Business Acumen: Ability to understand the big picture and the success criteria, stay focused to achieve goals, conduct systematic and accurate research, get into details, prevent avoidable failures. A passion for innovation and a commitment to staying up-to-date with the latest technological advancements in Generative AI.
- Communications: Strong technical communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
TBD