Country/Region:  IN
Requisition ID:  11485
Work Model: 
Position Type: 
Salary Range: 

Title:  Sr Solution Architect




  • Defining, designing and delivering ML architecture patterns operable in native and hybrid cloud architectures.
  • Research, analyze, recommend and select technical approaches to address challenging development and data integration problems related to ML Model training and deployment in Enterprise Applications.
  • Perform research activities to identify emerging technologies and trends that may affect the Data Science/ ML life-cycle management in enterprise application portfolio
  • Basic knowledge in LLM but AI, NLP and deep learning should be strong
  • Good with Associate architect or solution architect but no for Technical Lead.


  • Hands-on programming and architecture capabilities in Python, Java, R, or SCALA
  • Minimum 6+ years of Experience in Enterprise applications development (Java, . Net)
  • Experience in implementing and deploying
  • Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc. )
  • Strong hands-on experience with statistical packages and ML libraries (e. g. R, Python scikit learn, Spark MLlib, etc. )
  • Experience in effective data exploration and visualization (e. g. Excel, Power BI, Tableau, Qlik, etc. )
  • Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc. )
  • Hands on experience in RDBMS, NoSQL, big data stores like: Elastic, Cassandra, Hbase, Hive, HDFS
  • Work experience as Solution Architect/Software Architect/Technical Lead roles
  • Experience with open source software.
  • Excellent problem-solving skills and ability to break down complexity.
  • Ability to see multiple solutions to problems and choose the right one for the situation.
  • Excellent written and oral communication skills.
  • Demonstrated technical expertise around architecting solutions around AI, ML, deep learning and related technologies.
  • Developing AI/ML models in real-world environments and integrating AI/ML using Cloud native or hybrid technologies into large-scale enterprise applications.
  • In-depth experience in AI/ML and Data analytics services offered on Amazon Web Services and/or Microsoft Azure cloud solution and their interdependencies.
  • Specializes in at least one of the AI/ML stack (Frameworks and tools like MxNET and Tensorflow, ML platform such as Amazon SageMaker for data scientists, API-driven AI Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call).
  • Demonstrated experience developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.