E
Senior AI Engineer
E-Solutions
10 hours ago
Full-time
On-site
East New York, New York, United States
Senior AI Engineer
Location: Summit, NJ (Candidate has to go onsite only on need bases like once in a month or twice in a month) Role Summary: We are looking for a Senior AI Engineer to design, build, and run production AI solutions, including AI agents, retrieval-augmented generation (RAG), and LLM-powered automation. You will take use cases from discovery to production, making sure solutions are reliable, secure, and cost-effective. Key Responsibilities: Design and build AI agents and multi-step agentic workflows that automate business processes. Integrate LLMs with internal systems and data through APIs and MCP (Model Context Protocol). Build RAG, vector search, and embedding pipelines over documents and knowledge bases. Develop document processing pipelines to extract and validate structured data. Implement output validation, evaluation frameworks, and human-in-the-loop review. Build AI observability covering quality, latency, failure rates, and cost, with alerting. Work with data engineering teams on AI-ready data pipelines and models. Enforce data security, privacy, and PII handling across AI solutions. Own CI/CD, infrastructure-as-code, and deployment of AI services. Work with business stakeholders to scope use cases and define success metrics. Write architecture decision records, review code, and mentor engineers. Required Qualifications: 8+ years in software, data, or ML engineering, including 2+ years delivering LLM or GenAI solutions to production. Strong Python and SQL skills. Hands-on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI), prompt engineering, and structured outputs. Proven experience with RAG, vector databases, and embeddings. Experience building AI agents or agentic workflows. Solid data engineering background with a cloud data platform (Snowflake, Databricks, or similar), orchestration (Airflow or similar), and dbt. Production experience on AWS, Azure, or GCP, with Docker, CI/CD, and Terraform. Understanding of data security, privacy, and governance. Strong communication skills with both technical and non-technical audiences. Preferred Qualifications: Experience building MCP servers or gateways. Intelligent document processing or OCR experience. MLOps experience, including feature stores, model deployment, and GPU inference. Experience with AI evaluation, observability, and cost optimization. Background in financial services or another regulated industry. Master's degree in Computer Science, AI, or a related field. Cloud or data platform certifications (AWS ML, Snowflake, Azure AI). Regular use of AI-assisted development tools such as Claude Code or GitHub Copilot.
Location: Summit, NJ (Candidate has to go onsite only on need bases like once in a month or twice in a month) Role Summary: We are looking for a Senior AI Engineer to design, build, and run production AI solutions, including AI agents, retrieval-augmented generation (RAG), and LLM-powered automation. You will take use cases from discovery to production, making sure solutions are reliable, secure, and cost-effective. Key Responsibilities: Design and build AI agents and multi-step agentic workflows that automate business processes. Integrate LLMs with internal systems and data through APIs and MCP (Model Context Protocol). Build RAG, vector search, and embedding pipelines over documents and knowledge bases. Develop document processing pipelines to extract and validate structured data. Implement output validation, evaluation frameworks, and human-in-the-loop review. Build AI observability covering quality, latency, failure rates, and cost, with alerting. Work with data engineering teams on AI-ready data pipelines and models. Enforce data security, privacy, and PII handling across AI solutions. Own CI/CD, infrastructure-as-code, and deployment of AI services. Work with business stakeholders to scope use cases and define success metrics. Write architecture decision records, review code, and mentor engineers. Required Qualifications: 8+ years in software, data, or ML engineering, including 2+ years delivering LLM or GenAI solutions to production. Strong Python and SQL skills. Hands-on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI), prompt engineering, and structured outputs. Proven experience with RAG, vector databases, and embeddings. Experience building AI agents or agentic workflows. Solid data engineering background with a cloud data platform (Snowflake, Databricks, or similar), orchestration (Airflow or similar), and dbt. Production experience on AWS, Azure, or GCP, with Docker, CI/CD, and Terraform. Understanding of data security, privacy, and governance. Strong communication skills with both technical and non-technical audiences. Preferred Qualifications: Experience building MCP servers or gateways. Intelligent document processing or OCR experience. MLOps experience, including feature stores, model deployment, and GPU inference. Experience with AI evaluation, observability, and cost optimization. Background in financial services or another regulated industry. Master's degree in Computer Science, AI, or a related field. Cloud or data platform certifications (AWS ML, Snowflake, Azure AI). Regular use of AI-assisted development tools such as Claude Code or GitHub Copilot.