Senior AI Developer

Responsibilities:

• Lead end‑to‑end development of AI/ML solutions from discovery and PoC through production, monitoring, and continuous improvement.
• Build GenAI applications (e.g., RAG, summarization, code assistants, document intelligence) that accelerate engineering and project workflows.
• Design and implement data pipelines and feature stores; integrate structured, unstructured, and geospatial data at scale.
• Develop scalable APIs/microservices for model serving and orchestration using Python and modern frameworks.
• Implement ML Ops (CI/CD, containers, model registry, AWS/GCP as needed) and managed AI services (e.g., Azure OpenAI).
• Ensure security, privacy, and responsible AI practices observability, retraining) to ensure reliable deployments.
• Leverage cloud platforms (AZURE preferred; including governance, model risk management, and bias/robustness checks.
• Collaborate with cross‑functional teams to turn requirements into technical designs, delivery plans, and measurable outcomes.
• Mentor developers and data scientists; contribute to coding standards, reusable components, and best practices.
• Document architecture, decisions, and operating procedures for maintainability and auditability.

Requirements:

• Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or related field (or equivalent experience).
• 6+ years in software/AI development, with 3+ years building production ML/AI systems.
• Strong Python skills; experience with PyTorch or TensorFlow and modern GenAI stacks (e.g., LangChain/LlamaIndex).
• Hands‑on with LLMs and RAG (prompting, evaluation, vector search, guardrails); experience with vector databases (e.g., FAISS, Milvus, Pinecone).
• Proficient in data engineering (SQL, ETL/ELT, Spark or similar), APIs, and microservices.
• Experience with Docker, Kubernetes, CI/CD (GitHub Actions/Azure DevOps/GitLab), and model monitoring.
• Cloud proficiency—Azure preferred (Azure OpenAI, Cognitive Search, Azure ML); AWS/GCP a plus.
• Solid understanding of security, compliance, and responsible AI considerations in enterprise environments.
• Excellent communication and stakeholder engagement skills; ability to lead technical delivery and coach others.