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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformJenkinsKubernetesPySparkPythonSQLTerraform
About the role
Key responsibilities & impact- Design and implement AI/Gen AI applications, systems, and infrastructure across major clouds (Azure, AWS and GCP)
- Collaborate with data engineers & build AI/ML models.
- Collaborate with clients & stakeholders to translate business and functional requirements into robust, scalable, operable solutions.
- Participate in architectural decisions, contribute to the development of architectures for industry-wide use cases, and design architectures for AI/ML and Generative AI
- Set the standards for engineering best practices.
- Identify opportunities where generative AI can provide value and solve business problems.
- Responsible for creating POCs and POVs across horizontals and industry use cases.
- Write high-quality, efficient, testable code in Python and other languages.
- Stay up to date with the latest AI trends and evaluate state-of-the-art AI technologies/framework to drive innovation.
- Facilitate design and architecture workshops and mentor AI engineers in coding best practices and problem-solving.
Requirements
What you’ll need- A minimum of 3-5 years in building and deploying AI and Gen AI solutions on-premises or on cloud platforms.
- Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related field.
- Hand-on experience in deploying AI/ML solutions on different cloud platforms like Azure, AWS and/or Google Cloud.
- Experience in using and orchestration LLM models on cloud platforms i.e., OpenAI @ Azure/AWS Bedrock/ GCP Vertex AI or Gemini AI
- Experience in Agentic frameworks building and deploying (e.g. Semantic Kernel, CrewAI, LangGraph etc.)
- Experience in writing SQL and data modelling.
- Experience in designing and implementation of AI solution using microservice based architecture.
- Understanding of machine learning, deep learning, NLP and GenAI.
- Strong programming skills in Python and/or pyspark.
- Proven experience in integrating authentication security measures within machine learning operations and applications.
- Excellent problem-solving skills and ability to connect AI capabilities to business value.
- Strong communication and presentation skills.
- Proven experience in AI/ML solution deployment process on Kubernetes, Web Apps, Databricks or on similar platforms.
- Familiarity with MLOps concepts and tech stack.
- Good to know code versioning, MLFlow, batch prediction and real-time end point workflows.
- Familiarity with Azure DevOps / GitHub actions/ Jenkins / Terraform / AWS CFT etc.
- Familiarity with Responsible AI concepts
Benefits
Comp & perks- Competitive salary
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI applicationsGen AI applicationsAI/ML modelsPythonSQLdata modelingmicroservice architecturemachine learningdeep learningnatural language processing
Soft Skills
problem-solvingcommunicationpresentationcollaborationmentoring
Certifications
Bachelor’s degreeMaster’s degree