AI Engineer

We are seeking a Senior AI Engineer with strong hands-on experience in AI/ML, Generative AI, LLMs, RAG, Agentic AI, NLP, and healthcare solutions. The candidate will be responsible for designing, developing, deploying, and optimizing production-grade AI applications using healthcare data such as EHR/EMR, claims, clinical notes, and medical documents., * Design and develop scalable AI/ML and Generative AI solutions for healthcare use cases.

• Build production-grade LLM applications, RAG pipelines, AI agents, and conversational AI systems.
• Work with healthcare data including EHR/EMR, claims, clinical notes, medical documents, and structured/unstructured data.
• Implement prompt engineering, embeddings, vector search, semantic search, reranking, and knowledge retrieval.
• Develop agentic AI solutions using LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.
• Fine-tune/customize LLMs using LoRA, PEFT, or similar techniques.
• Build data pipelines for AI/ML ingestion, preprocessing, enrichment, training, and evaluation.
• Integrate AI applications with APIs, databases, enterprise applications, and healthcare platforms.
• Implement LLM evaluation, observability, monitoring, guardrails, hallucination detection, and performance optimization.
• Deploy solutions on AWS, Azure, or Google Cloud Platform using MLOps/LLMOps practices.
• Implement CI/CD, model versioning, automated testing, monitoring, and production deployment.
• Ensure compliance with HIPAA, healthcare security/privacy, data governance, and responsible AI requirements.
• Provide technical leadership, architecture/design guidance, and mentor junior engineers.

• 6+ years of AI/ML or software engineering experience with production AI solutions.
• Strong Python programming skills.
• Strong knowledge of Machine Learning, Deep Learning, NLP, LLMs, and Generative AI.
• Hands-on experience with RAG and/or Agentic AI.
• Experience with vector databases such as Pinecone, FAISS, pgvector, Qdrant, or Azure AI Search.
• Experience with LLM platforms/models such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs.
• Experience with AWS, Azure, or Google Cloud Platform.
• Strong understanding of REST APIs, microservices, Docker, Kubernetes, Git, and CI/CD.
• Experience with model evaluation, monitoring, observability, and production troubleshooting.

Healthcare Domain Experience :

• Experience in Healthcare, Life Sciences, Medical Technology, Health Insurance, or Clinical Applications.
• Knowledge of EHR/EMR, Claims, Clinical Notes, HL7/FHIR, ICD, CPT/HCPCS, and medical terminology.
• Understanding of healthcare privacy, security, compliance, and data governance.
• Knowledge of FHIR, SNOMED CT, LOINC, UMLS, or similar healthcare standards is preferred.
• Experience with healthcare AI use cases such as clinical documentation, medical summarization, patient engagement, claims processing, care management, or clinical decision support is a plus.

Preferred Technologies :

• LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI
• PyTorch, TensorFlow, Hugging Face
• RAG, Graph RAG, Knowledge Graphs, Hybrid Search
• Azure OpenAI, Azure AI Foundry, AWS Bedrock, SageMaker
• Databricks, Spark, Snowflake
• MLflow, PostgreSQL, MongoDB, Redis, Neo4j
• Kafka, Terraform, Docker, Kubernetes
• LLM evaluation/observability frameworks
• Responsible AI, explainability, bias detection, and AI governance

Education :

Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Key Skills :