Senior AI​/ML Engineer

Soni's client is seeking an Artificial Intelligence / Machine Learning Engineer to design, build, deploy, and support enterprise-scale AI and ML solutions across cloud and hybrid environments. This is a highly hands‑on role focused on delivering scalable, secure, and high-performing AI solutions aligned with business and technology objectives.

The ideal candidate will have experience developing production‑grade AI applications, LLM‑powered solutions, and agentic workflows while collaborating with cross‑functional technical and business teams.

• Design, develop, and maintain production‑grade AI and ML solutions across cloud and hybrid platforms
• Build end‑to‑end AI application pipelines including data ingestion, prompt engineering, model evaluation, deployment, and monitoring
• Develop and support LLM‑powered applications and agentic workflows
• Collaborate with engineering, data, and business stakeholders to translate requirements into AI and ML solutions
• Write scalable, maintainable, and high‑quality Python code for AI and ML applications
• Optimize performance, scalability, reliability, and cost efficiency of AI and ML services
• Integrate AI and ML applications with enterprise APIs, data lakes, data warehouses, retrieval systems (RAG), and streaming platforms
• Support AI solution lifecycle management including versioning, prompt iteration, evaluation, and production support
• Apply security, governance, compliance, and data privacy best practices across AI and ML systems
• Participate in technical architecture and solution design discussions
• Stay current on advancements in AI, ML, LLMs, cloud engineering, and orchestration technologies

• 5+ years of experience building and deploying AI and ML solutions
• Strong hands‑on experience developing AI and ML applications within cloud environments
• Advanced Python programming skills focused on AI/ML engineering and LLM application development
• Experience building and supporting LLM‑powered applications, agentic workflows, and AI orchestration pipelines
• Experience integrating LLM applications with enterprise data sources and retrieval systems (RAG)
• Hands‑on experience with AI orchestration and observability frameworks such as Lang Chain, Lang Smith, Pydantic AI, or similar technologies
• Strong understanding of cloud security, AI governance, data privacy, and enterprise AI compliance practices

• Experience supporting enterprise AI initiatives within professional services or regulated environments
• Familiarity with vector databases, embedding models, semantic search, and AI evaluation frameworks
• Experience with containerization and deployment technologies such as Docker and Kubernetes
• Exposure to MLOps and AI observability best practices
• Experience integrating AI systems into enterprise business workflows and knowledge management platforms