Healthcare AI Solution Architect

Title

Experience

Location

Healthcare AI Solution Architect

Key Responsibilities

• Architect and deliver

  end-to-end AI/ML solutions

  for healthcare and payer use cases.
• Apply

  MLOps methodologies

  to streamline model lifecycle management.
• Leverage

  Cognitive AI techniques

  including NLP, Computer Vision, Speech, and Conversational AI.
• Develop and implement

  Document AI

  and

  Generative AI

  solutions, including custom LLMs.
• Ensure seamless integration of AI solutions into

  cloud platforms

  (AWS, Azure, GCP).
• Maintain

  robustness, scalability, and reliability

  of production-grade ML systems.
• Provide

  technical leadership and mentorship

  to AI/ML teams.
• Collaborate with cross-functional teams to transition prototypes into scalable products.
• Prepare comprehensive documentation for architecture, design, and implementation.

Mandatory Skills & Qualifications:

• 8+ years in AI/ML

  , with

  3+ years in healthcare/payer AI

  .
• Proven expertise in

  AI, ML, MLOps, Text Analytics, Generative AI

  .
• Strong programming skills in

  Python and Java

  .
• Experience with ML frameworks:

  TensorFlow, PyTorch, Keras, Scikit-learn

  .
• Hands-on with cloud platforms:

  AWS, Azure, GCP

  .
• Proficient in ML architectures:

  Ensemble Models, SVM, CNN, RNN, Transformers

  .
• NLP tools:

  NLTK, SpaCy, Gensim

  .
• MLOps tools:

  Kubeflow, MLflow, Azure ML

  .
• Experience in

  Responsible AI

  ,

  LangChain

  , and

  Vector Databases

  .
• Workflow tools:

  Airflow

  .
• Microservices architecture and API development using

  FastAPI, Flask, Django

  .
• Database expertise:

  SQL, NoSQL (MongoDB, Postgres, Neo4j)

  .

Desirable Skills:

• Degree in

  Statistics, Mathematics, Computer Science

  , or related field (Bachelor’s/Master’s/PhD).
• Experience with

  statistical and data mining techniques

  : GLM, Regression, Random Forest, Boosting, etc.
• Advanced ML algorithms:

  clustering, decision trees, neural networks, simulation, scenario analysis

  .
• Experience with

  R, Python

  for statistical computing.
• Contributions to

  open-source AI/ML projects

  or published research.
• Data visualization tools:

  Matplotlib, ggplot

  .
• Exposure to

  Big Data platforms

  : Hadoop, Spark, Kafka.
• Strong

  problem-solving

  ,

  collaboration

  , and

  communication

  skills.

• Architect-level certifications

  are a plus.