AI Engineer

We are seeking an experienced AI Engineer with strong hands-on experience in Prompt Engineering, LLM application development, Agentic AI, RAG, and AI response optimization.

The ideal candidate will have experience designing reliable, context-aware AI solutions, integrating LLMs with enterprise systems, developing AI agents and tool-calling workflows, and improving model response quality, accuracy, and reliability.

Key Responsibilities

• Design, develop, and optimize prompts for Large Language Models (LLMs) to improve accuracy, reliability, and business outcomes.
• Build and configure Agentic AI solutions supporting planning, reasoning, memory, and multi-step task execution.
• Develop and integrate MCP (Model Context Protocol) tools that enable AI agents to securely interact with enterprise systems, APIs, and data sources.
• Design agent architectures, tool-calling frameworks, retrieval mechanisms, and context-management strategies.
• Develop AI-powered applications using LLM APIs, RAG workflows, enterprise data sources, and backend services.
• Implement Retrieval-Augmented Generation (RAG), knowledge grounding, embeddings, vector databases, and semantic search.
• Evaluate and improve LLM responses for accuracy, relevance, completeness, tone, and instruction following.
• Develop evaluation frameworks and prompt-testing methodologies to measure AI agent performance, quality, and reliability.
• Apply NLP concepts, hallucination mitigation techniques, prompt-injection protection, guardrails, and responsible AI practices.
• Collaborate with product managers, architects, and engineering teams to translate business requirements into AI-driven solutions.
• Ensure AI solutions follow security, compliance, governance, and responsible AI standards.
• Support deployment, monitoring, troubleshooting, and continuous improvement of AI agents and MCP-enabled workflows.
• Contribute to architecture reviews, technical design documentation, and AI engineering best practices.

Required Skills

• 9+ years of professional IT/software engineering experience.
• Strong hands-on Prompt Engineering experience, including prompt templates, system prompts, few-shot prompting, and response tuning.
• Hands-on experience with LLMs such as GPT, Claude, Gemini, Llama, or similar models.
• Experience developing AI applications using LLM APIs, RAG workflows, enterprise data sources, and backend services.
• Strong programming experience with Python, Java, JavaScript, or similar languages.
• Knowledge of RAG, embeddings, vector databases, semantic search, and knowledge retrieval workflows.
• Experience evaluating and optimizing LLM responses.
• Understanding of NLP, hallucination mitigation, prompt injection risks, guardrails, and responsible AI.
• Experience integrating AI solutions with APIs, backend services, and enterprise systems.
• Knowledge of healthcare data privacy and secure sensitive-data handling, including:
  • HIPAA-aligned practices
  • PHI/PII protection
  • Data minimization
  • De-identification
  • Data masking
  • Access controls
  • Auditability
  • Responsible use of healthcare data in AI workflows

Preferred Skills

• Experience with MCP servers / Model Context Protocol.
• Experience building and deploying Agentic AI solutions in production.
• Experience with cloud platforms and production AI deployments.
• Experience integrating AI agents with healthcare systems, electronic health records, or other regulated-industry systems.
• Experience with healthcare data and regulated enterprise environments.
• Experience with AI evaluation frameworks and automated prompt testing.
• Experience with AI architecture, technical design, and production monitoring.