Job Summary
Experienced AIML Architect to design and implement cutting-edge AI/ML solutions leveraging AWS and other modern technologies. The ideal candidate will have strong expertise in building scalable models, deploying them in production, and driving innovation across multiple industry verticals.
Responsibilities
- Design and implement AI/ML solutions for complex business problems across domains like Banking, Finance, Telecom, Retail, LSH and Technology.
- Develop and optimize Machine Learning and Deep Learning models using frameworks such as TensorFlow, Keras, PyTorch.
- Build and maintain scalable data pipelines and ML workflows using Python, Spark, PySpark, and AWS services.
- Deploy and monitor models on AWS
- Transform prototypes into robust, production-ready solutions.
- Deep expertise in developing, testing, deploying, and monitoring AI applications and infrastructure using Git and robust CI/CD pipelines.
- Work with containerization and orchestration tools like Docker and Kubernetes.
- Apply advanced statistical analysis, text mining, and machine log processing techniques.
- Collaborate with cross-functional teams to ensure alignment with business goals
-Knowledge / Experience on AWS Agentic AI Services
Key Responsibilities
Experienced AIML Architect to design and implement cutting-edge AI/ML solutions leveraging AWS and other modern technologies. The ideal candidate will have strong expertise in building scalable models, deploying them in production, and driving innovation across multiple industry verticals.
Responsibilities
- Design and implement AI/ML solutions for complex business problems across domains like Banking, Finance, Telecom, Retail, LSH and Technology.
- Develop and optimize Machine Learning and Deep Learning models using frameworks such as TensorFlow, Keras, PyTorch.
- Build and maintain scalable data pipelines and ML workflows using Python, Spark, PySpark, and AWS services.
- Deploy and monitor models on AWS
- Transform prototypes into robust, production-ready solutions.
- Deep expertise in developing, testing, deploying, and monitoring AI applications and infrastructure using Git and robust CI/CD pipelines.
- Work with containerization and orchestration tools like Docker and Kubernetes.
- Apply advanced statistical analysis, text mining, and machine log processing techniques.
- Collaborate with cross-functional teams to ensure alignment with business goals
-Knowledge / Experience on AWS Agentic AI Services
Skill Requirements
Qualifications, Skills and Competencies
Education & Experience:-
Bachelor’s/Master’s in engineering (pref comp science with specialization in AI/ML)
Technical / Functional Skills:-
AI/ML Development: TensorFlow, Keras, PyTorch, Scikit-learn, Spark ML.
Programming: Python (expert), R (working knowledge), Spark.
Data Handling: Pandas, NumPy, PySpark.
ML Ops: CI/CD pipelines, model deployment, monitoring.
Statistical Analysis: Strong foundation in statistics and data-driven decision-making.
AWS Agentic Workflows: Experience using AWS Bedrock and Agent Core to build AI agents
Generative AI: Amazon Bedrock (Agents, Knowledge Bases, Guardrails), Agent Core
DevOps & Tools: Git, CI/CD (Deep Experience with GitHub Actions / AWS CodePipeline), Terraform or CloudFormation (IaC), Artifact Management.
Domain Knowledge: Exposure to supervised, unsupervised, and reinforcement learning.
Integration Standards: REST APIs, OData, OpenAPI (Swagger) Specifications, JSON.
Enterprise identity patterns : IAM roles/SCPs, Cognito federation, Okta SSO
Core Competencies (Soft Skills):
- Strong communication & presentation- Analytical, client-first mindset
- Leadership & stakeholder management- Ability to work in global, fast-paced environment.
- Provide architectural leadership in client workshops, technical assessments, and solution reviews.
- Advise clients on AI strategy, modernization roadmaps, and responsible AI adoption.