Artificial Intelligence Engineer

Job Summary

We are seeking a highly skilled GenAI / Agentic AI Engineer to design, develop, and deploy intelligent AI-driven solutions that leverage Large Language Models (LLMs), prompt engineering, and agentic workflows. The ideal candidate will work closely with architects and business stakeholders to build AI agents capable of reasoning, decision-making, and orchestrating automation workflows across enterprise systems.

Key Responsibilities

• Design, develop, and deploy GenAI-powered solutions using LLMs like OpenAI GPT, Anthropic Claude or Llama .
• Build and configure Agentic AI systems that can plan, reason, and interact with APIs, databases, and automation platforms.
• Develop and optimize prompt chains, retrieval-augmented generation (RAG) pipelines, and context-aware memory architectures for dynamic agent behavior.
• Integrate AI agents with automation and orchestration tools such as UiPath, Power Automate, AWS Lambda, or custom APIs.
• Write clean, maintainable code in Python and C# for backend integrations, automation bridges, and service deployments.
• Collaborate with business and technical teams to identify use cases suitable for AI-driven automation.
• Implement AI governance, compliance, and data security standards (HIPAA, SOC 2, GDPR as applicable).
• Fine-tune or customize models for Healthcare domain-specific applications
• Monitor, evaluate, and optimize model performance, latency, and cost efficiency.
• Create proof of concepts (POCs) and transition them into production-grade solutions.

Required Skills & Experience

• Strong hands-on experience with Generative AI frameworks and APIs (OpenAI, Anthropic, Hugging Face, Azure OpenAI, or Vertex AI).
• Proficiency in Python (for AI development, integration, and automation) and C# (for enterprise and backend systems).
• Knowledge of Agentic AI frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel).
• Experience building AI copilots, or autonomous multi-agent systems.
• Strong understanding of prompt engineering, context management, and reasoning-based agent orchestration.
• Familiarity with LLM integration in enterprise automation environments (UiPath, Power Automate, AWS Connect, or REST APIs).
• Experience working with vector databases (Pinecone, FAISS, Weaviate, Chroma) and document retrieval (RAG) techniques.
• Knowledge of cloud AI services (AWS AI, Azure Cognitive Services, GCP Vertex AI).
• Excellent debugging, problem-solving, and cross-functional collaboration skills.

Good-to-Have Skills

• Experience in Healthcare AI solutions (e.g., RCM, claims, or benefit verification).
• Familiarity with Docker, REST APIs, microservices, and serverless architectures.
• Understanding of guardrails, LLMOps, and model evaluation frameworks.
• Basic exposure to machine learning lifecycle tools (MLflow, DVC).

Education

• Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• Certifications in AI / GenAI / Cloud AI platforms (OpenAI, Azure, AWS) are an advantage.