AI Engineer

As an AI Engineer at […] you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively.

• Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring.
• Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals.
• Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks.
• Develop and integrate AI models into production systems (APIs, microservices, cloud deployments).
• Optimize models/solutions for performance, scalability, robustness and cost-efficiency.
• Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation.
• Document model design, experiments, data provenance and solution rationale.
• Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas.
• Work directly with clients to understand problem statements, translate business requirements into AI solution