Agentic AI-Senior Engineer

About this role

What Skills Are ExpectedProgramming & Software Engineering: Expertise in Python (and optionally Java, JavaScript, or C#), unit testing, and version control (Git).AI/ML Knowledge: Solid grasp of machine learning and AI concepts, model behavior, and experience with NLP or chatbots.Prompt Engineering: Experience crafting and iterating prompts, including few-shot examples and output formatting techniques.RAG and Data Handling: Familiarity with embedding models, vector databases, and unstructured data processing.API and Integration Skills: Building and consuming RESTful APIs, microservices, and handling JSON/XML data formats.Data Structures & Algorithms: Knowledge of lists, dictionaries, trees/graphs, and their application in efficient agent design.Debugging & Problem-Solving: Strong troubleshooting abilities to distinguish between model and code issues.Agile and Collaborative Mindset: Comfortable working in sprints, collaborating across teams, and communicating technical needs.Domain Adaptability: Ability to quickly learn new industry concepts for tailored agent solutions.Attention to Detail & Quality: Consideration of edge cases, proper data handling, and thorough testing.Ethical Awareness: Recognize bias, confidentiality issues, and flag questionable requests.

Key Technology Capabilities•Languages & Frameworks: Mastery of Python for AI/ML, with exposure to JavaScript/TypeScript, FastAPI, or Flask for APIs.•AI/ML Tools: Experience with AI model APIs (OpenAI, Azure OpenAI), and ML frameworks like PyTorch or TensorFlow.•Agent Development Libraries: Hands-on with LangChain or similar frameworks for prompt management and agent logic.•Databases & Data Access: Working with SQL, NoSQL, and vector databases (e.g., Pinecone, Weaviate) for data retrieval.•DevOps & Deployment: Familiarity with Docker, CI/CD, and cloud deployment (AWS, Azure, GCP, Lambda/Functions).•Version Control & Collaboration: Proficient with Git and DevOps platforms (GitHub, GitLab, ...