Senior AI Engineer

Key details

• Design, build, and maintain AI-powered applications, services, and integrations as part of the AI Engineering team
• Implement solutions focused on AI agents, agentic workflows, automation, LLM-based applications, and AI-assisted business processes
• Build and integrate AI applications using technologies such as Python (FastAPI/Flask/Django) or equivalent frameworks, React frontends, and relevant AI/ML frameworks
• Implement AI solutions using AWS AI/ML services, including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker, and other AWS services for model hosting, inference, orchestration, data processing, monitoring, and security
• Work closely with the AI Tech Lead to align on architecture, technology choices, engineering standards, AI patterns, and rollout approaches
• Provide technical input and guidance to other engineers on AI implementation patterns, code quality, testing, observability, and production readiness
• Develop and integrate AI agents that interact with internal APIs, business workflows, enterprise systems, knowledge bases, and external tools in a safe and controlled way
• Build and maintain RAG-based solutions, including document ingestion, chunking, embeddings, vector search, retrieval logic, reranking, and grounding techniques
• Support the development and deployment of machine learning models and AI solutions into production environments
• Contribute to ML pipelines and MLOps practices, including data preparation, model training, experiment tracking, model deployment, monitoring, evaluation, and lifecycle management
• Integrate LLMs through APIs
• Implement AI evaluation approaches for LLM outputs, RAG quality, agent behavior, model performance, hallucination detection, safety, and reliability
• Support prompt engineering, prompt versioning, function calling, tool use, memory patterns, guardrails, and LLM application testing
• Design and consume APIs and contribute to cloud-based, scalable backend architectures
• Collaborate with product managers, engineers, data scientists, DevOps, security, and business stakeholders to deliver practical AI solutions
• Write clean, maintainable, testable, and well-documented code
• Support production rollouts, troubleshooting, monitoring, optimization, and continuous improvement of AI systems
• Stay current with modern AI technologies, frameworks, models, and engineering practices, and bring practical recommendations to the team
• Company mission
• Information not specified